Random+Forest.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the pandas package, then use the \"read_csv\" function to read\n",
    "# the labeled training data\n",
    "import pandas as pd \n",
    "from sklearn.model_selection import train_test_split\n",
    "data = pd.read_csv(\"Downloads/deceptive-opinion.csv\")\n",
    "\n",
    "# Splitting the dataset into train and test set\n",
    "train, test = train_test_split(data,test_size = 0.2)\n",
    "train = train.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['index', 'deceptive', 'hotel', 'polarity', 'source', 'text'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.shape\n",
    "train.columns.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>deceptive</th>\n",
       "      <th>hotel</th>\n",
       "      <th>polarity</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>854</td>\n",
       "      <td>truthful</td>\n",
       "      <td>conrad</td>\n",
       "      <td>negative</td>\n",
       "      <td>Web</td>\n",
       "      <td>The Conrad has all the right stuff - great bed...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>25</td>\n",
       "      <td>truthful</td>\n",
       "      <td>conrad</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>Arrived on 06/04/05, greeted by friendly doorm...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>494</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>homewood</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>Homewood Suites by Hilton Chicago Downtown is ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>755</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>palmer</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>The Palmer House Hilton hotel takes luxury to ...</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>560</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>talbott</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>This hotel was an absolute dream to stay in. I...</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>804</td>\n",
       "      <td>truthful</td>\n",
       "      <td>hyatt</td>\n",
       "      <td>negative</td>\n",
       "      <td>Web</td>\n",
       "      <td>They allowed parties to go on all night and bo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>986</td>\n",
       "      <td>truthful</td>\n",
       "      <td>hardrock</td>\n",
       "      <td>negative</td>\n",
       "      <td>Web</td>\n",
       "      <td>We stayed at this Hotel in February 2010. The ...</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>180</td>\n",
       "      <td>truthful</td>\n",
       "      <td>affinia</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>My husband &amp; I stayed at the Fitzpatrick in ea...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>599</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>ambassador</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>O.M.G best hotel ever ! i've stayed at various...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>822</td>\n",
       "      <td>truthful</td>\n",
       "      <td>fairmont</td>\n",
       "      <td>negative</td>\n",
       "      <td>Web</td>\n",
       "      <td>I stayed at the Chicago Fairmont for four nigh...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1471</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>monaco</td>\n",
       "      <td>negative</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>I decided to spend the extra money booking a r...</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>527</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>knickerbocker</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>My family really enjoyed this hotel the weeken...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1499</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>sofitel</td>\n",
       "      <td>negative</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>Sofitel not-so-luxury Hotels I recently checke...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>64</td>\n",
       "      <td>truthful</td>\n",
       "      <td>conrad</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>This was a weekend trip for my friends and I. ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1198</td>\n",
       "      <td>truthful</td>\n",
       "      <td>amalfi</td>\n",
       "      <td>negative</td>\n",
       "      <td>Web</td>\n",
       "      <td>Overview: --Overrated hotel in a premium locat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1008</td>\n",
       "      <td>truthful</td>\n",
       "      <td>hardrock</td>\n",
       "      <td>negative</td>\n",
       "      <td>Web</td>\n",
       "      <td>Not worth the price, even a little bit. A week...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>378</td>\n",
       "      <td>truthful</td>\n",
       "      <td>allegro</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>I loved this hotel - reasonable for downtown C...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1384</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>affinia</td>\n",
       "      <td>negative</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>I stayed at the Affnia hotel in Chicago and wa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1290</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>homewood</td>\n",
       "      <td>negative</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>DO NOT STAY AT THIS HOTEL!!!! I would have cer...</td>\n",
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       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>608</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>affinia</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>We stayed for two nights for a meeting. It is ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>749</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>allegro</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>My husband and I stayed at the Hotel Allegro C...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>24</td>\n",
       "      <td>truthful</td>\n",
       "      <td>hyatt</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>Check-in was fast, the room was perfect, and t...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1044</td>\n",
       "      <td>truthful</td>\n",
       "      <td>james</td>\n",
       "      <td>negative</td>\n",
       "      <td>Web</td>\n",
       "      <td>Just returned from the James Hotel after stayi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>105</td>\n",
       "      <td>truthful</td>\n",
       "      <td>homewood</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>i was in chicago from september 17-22 for a co...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>60</td>\n",
       "      <td>truthful</td>\n",
       "      <td>omni</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>Great hotel in heart of Chicago for business o...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1502</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>sofitel</td>\n",
       "      <td>negative</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>I stayed at the Sofitel Chicago Water Tower ho...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>886</td>\n",
       "      <td>truthful</td>\n",
       "      <td>swissotel</td>\n",
       "      <td>negative</td>\n",
       "      <td>Web</td>\n",
       "      <td>Three nights there on business. Hadn't realize...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>460</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>omni</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>The Omni Chicago Hotel is a very high quality ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1495</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>monaco</td>\n",
       "      <td>negative</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>We booked this trip several months in advance ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>219</td>\n",
       "      <td>truthful</td>\n",
       "      <td>ambassador</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>My wife and I stayed at the Ambassador East Ho...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1250</th>\n",
       "      <td>45</td>\n",
       "      <td>truthful</td>\n",
       "      <td>fairmont</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>I stayed at the Fairmont to attend a conferenc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1251</th>\n",
       "      <td>346</td>\n",
       "      <td>truthful</td>\n",
       "      <td>allegro</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>This is best hotel bargin in Chicago if you ar...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1252</th>\n",
       "      <td>766</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>palmer</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>Everything experienced at this hotel was grand...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1253</th>\n",
       "      <td>401</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>conrad</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>My wife and I booked a Deluxe Accessible Room ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1254</th>\n",
       "      <td>870</td>\n",
       "      <td>truthful</td>\n",
       "      <td>conrad</td>\n",
       "      <td>negative</td>\n",
       "      <td>Web</td>\n",
       "      <td>' Barely Average Hotel at Premium Price' This ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1255</th>\n",
       "      <td>188</td>\n",
       "      <td>truthful</td>\n",
       "      <td>affinia</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>The Affinia is virtually the perfect hotel for...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1256</th>\n",
       "      <td>1192</td>\n",
       "      <td>truthful</td>\n",
       "      <td>intercontinental</td>\n",
       "      <td>negative</td>\n",
       "      <td>Web</td>\n",
       "      <td>Spent three nights in Chicago at this property...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1257</th>\n",
       "      <td>1343</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>swissotel</td>\n",
       "      <td>negative</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>The Swissotel Chicago hotel aspires to be a to...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1258</th>\n",
       "      <td>216</td>\n",
       "      <td>truthful</td>\n",
       "      <td>hardrock</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>Stayed here for 4 nights in Apri. From check i...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1259</th>\n",
       "      <td>568</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>affinia</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>The Affinia hotel in Chicago was superb. the r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1260</th>\n",
       "      <td>718</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>monaco</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>This is a beautiful hotel with a great view of...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1261</th>\n",
       "      <td>422</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>fairmont</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>The atmosphere at this hotel is truly remarkab...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1262</th>\n",
       "      <td>1196</td>\n",
       "      <td>truthful</td>\n",
       "      <td>intercontinental</td>\n",
       "      <td>negative</td>\n",
       "      <td>Web</td>\n",
       "      <td>Good location and looks like a good property b...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1263</th>\n",
       "      <td>297</td>\n",
       "      <td>truthful</td>\n",
       "      <td>monaco</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>My initial thought of the hotel was, this plac...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1264</th>\n",
       "      <td>160</td>\n",
       "      <td>truthful</td>\n",
       "      <td>ambassador</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>Our stay at the Ambassador East Hotel was extr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1265</th>\n",
       "      <td>373</td>\n",
       "      <td>truthful</td>\n",
       "      <td>intercontinental</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>We got an awesome deal through Priceline for a...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1266</th>\n",
       "      <td>1552</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>intercontinental</td>\n",
       "      <td>negative</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>This hotel has a good name and a good location...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1267</th>\n",
       "      <td>751</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>intercontinental</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>This is a great place to stay while visiting C...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1268</th>\n",
       "      <td>1406</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>talbott</td>\n",
       "      <td>negative</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>We chose the Talbott Hotel primarily for the l...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1269</th>\n",
       "      <td>277</td>\n",
       "      <td>truthful</td>\n",
       "      <td>sofitel</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>Great beds, clean rooms, amazing bathroom, nif...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1270</th>\n",
       "      <td>1165</td>\n",
       "      <td>truthful</td>\n",
       "      <td>allegro</td>\n",
       "      <td>negative</td>\n",
       "      <td>Web</td>\n",
       "      <td>I usually stay at the Hotel Monaco but stayed ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1271</th>\n",
       "      <td>668</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>sofitel</td>\n",
       "      <td>positive</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>This hotel is beautiful, it is very modern and...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1272</th>\n",
       "      <td>261</td>\n",
       "      <td>truthful</td>\n",
       "      <td>sofitel</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>After some deliberation I booked the Sofitel W...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1273</th>\n",
       "      <td>1533</td>\n",
       "      <td>deceptive</td>\n",
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       "      <td>negative</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>My wife and I recently stayed at the Allegro h...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1274</th>\n",
       "      <td>43</td>\n",
       "      <td>truthful</td>\n",
       "      <td>conrad</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>My husband and I decided to take a trip to Chi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1275</th>\n",
       "      <td>1382</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>affinia</td>\n",
       "      <td>negative</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>Hello, I recently stayed at the Affinia hotel ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1276</th>\n",
       "      <td>74</td>\n",
       "      <td>truthful</td>\n",
       "      <td>fairmont</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>From the moment I stepped up to the front entr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1277</th>\n",
       "      <td>90</td>\n",
       "      <td>truthful</td>\n",
       "      <td>homewood</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>Just back from a business trip. The Homewood i...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1278</th>\n",
       "      <td>95</td>\n",
       "      <td>truthful</td>\n",
       "      <td>homewood</td>\n",
       "      <td>positive</td>\n",
       "      <td>TripAdvisor</td>\n",
       "      <td>Our first visit to Chicago and I really cannot...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1279</th>\n",
       "      <td>1510</td>\n",
       "      <td>deceptive</td>\n",
       "      <td>sofitel</td>\n",
       "      <td>negative</td>\n",
       "      <td>MTurk</td>\n",
       "      <td>I needed a place to stay for a business confer...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1280 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      index  deceptive             hotel  polarity       source  \\\n",
       "0       854   truthful            conrad  negative          Web   \n",
       "1        25   truthful            conrad  positive  TripAdvisor   \n",
       "2       494  deceptive          homewood  positive        MTurk   \n",
       "3       755  deceptive            palmer  positive        MTurk   \n",
       "4       560  deceptive           talbott  positive        MTurk   \n",
       "5       804   truthful             hyatt  negative          Web   \n",
       "6       986   truthful          hardrock  negative          Web   \n",
       "7       180   truthful           affinia  positive  TripAdvisor   \n",
       "8       599  deceptive        ambassador  positive        MTurk   \n",
       "9       822   truthful          fairmont  negative          Web   \n",
       "10     1471  deceptive            monaco  negative        MTurk   \n",
       "11      527  deceptive     knickerbocker  positive        MTurk   \n",
       "12     1499  deceptive           sofitel  negative        MTurk   \n",
       "13       64   truthful            conrad  positive  TripAdvisor   \n",
       "14     1198   truthful            amalfi  negative          Web   \n",
       "15     1008   truthful          hardrock  negative          Web   \n",
       "16      378   truthful           allegro  positive  TripAdvisor   \n",
       "17     1384  deceptive           affinia  negative        MTurk   \n",
       "18     1290  deceptive          homewood  negative        MTurk   \n",
       "19      608  deceptive           affinia  positive        MTurk   \n",
       "20      749  deceptive           allegro  positive        MTurk   \n",
       "21       24   truthful             hyatt  positive  TripAdvisor   \n",
       "22     1044   truthful             james  negative          Web   \n",
       "23      105   truthful          homewood  positive  TripAdvisor   \n",
       "24       60   truthful              omni  positive  TripAdvisor   \n",
       "25     1502  deceptive           sofitel  negative        MTurk   \n",
       "26      886   truthful         swissotel  negative          Web   \n",
       "27      460  deceptive              omni  positive        MTurk   \n",
       "28     1495  deceptive            monaco  negative        MTurk   \n",
       "29      219   truthful        ambassador  positive  TripAdvisor   \n",
       "...     ...        ...               ...       ...          ...   \n",
       "1250     45   truthful          fairmont  positive  TripAdvisor   \n",
       "1251    346   truthful           allegro  positive  TripAdvisor   \n",
       "1252    766  deceptive            palmer  positive        MTurk   \n",
       "1253    401  deceptive            conrad  positive        MTurk   \n",
       "1254    870   truthful            conrad  negative          Web   \n",
       "1255    188   truthful           affinia  positive  TripAdvisor   \n",
       "1256   1192   truthful  intercontinental  negative          Web   \n",
       "1257   1343  deceptive         swissotel  negative        MTurk   \n",
       "1258    216   truthful          hardrock  positive  TripAdvisor   \n",
       "1259    568  deceptive           affinia  positive        MTurk   \n",
       "1260    718  deceptive            monaco  positive        MTurk   \n",
       "1261    422  deceptive          fairmont  positive        MTurk   \n",
       "1262   1196   truthful  intercontinental  negative          Web   \n",
       "1263    297   truthful            monaco  positive  TripAdvisor   \n",
       "1264    160   truthful        ambassador  positive  TripAdvisor   \n",
       "1265    373   truthful  intercontinental  positive  TripAdvisor   \n",
       "1266   1552  deceptive  intercontinental  negative        MTurk   \n",
       "1267    751  deceptive  intercontinental  positive        MTurk   \n",
       "1268   1406  deceptive           talbott  negative        MTurk   \n",
       "1269    277   truthful           sofitel  positive  TripAdvisor   \n",
       "1270   1165   truthful           allegro  negative          Web   \n",
       "1271    668  deceptive           sofitel  positive        MTurk   \n",
       "1272    261   truthful           sofitel  positive  TripAdvisor   \n",
       "1273   1533  deceptive           allegro  negative        MTurk   \n",
       "1274     43   truthful            conrad  positive  TripAdvisor   \n",
       "1275   1382  deceptive           affinia  negative        MTurk   \n",
       "1276     74   truthful          fairmont  positive  TripAdvisor   \n",
       "1277     90   truthful          homewood  positive  TripAdvisor   \n",
       "1278     95   truthful          homewood  positive  TripAdvisor   \n",
       "1279   1510  deceptive           sofitel  negative        MTurk   \n",
       "\n",
       "                                                   text  \n",
       "0     The Conrad has all the right stuff - great bed...  \n",
       "1     Arrived on 06/04/05, greeted by friendly doorm...  \n",
       "2     Homewood Suites by Hilton Chicago Downtown is ...  \n",
       "3     The Palmer House Hilton hotel takes luxury to ...  \n",
       "4     This hotel was an absolute dream to stay in. I...  \n",
       "5     They allowed parties to go on all night and bo...  \n",
       "6     We stayed at this Hotel in February 2010. The ...  \n",
       "7     My husband & I stayed at the Fitzpatrick in ea...  \n",
       "8     O.M.G best hotel ever ! i've stayed at various...  \n",
       "9     I stayed at the Chicago Fairmont for four nigh...  \n",
       "10    I decided to spend the extra money booking a r...  \n",
       "11    My family really enjoyed this hotel the weeken...  \n",
       "12    Sofitel not-so-luxury Hotels I recently checke...  \n",
       "13    This was a weekend trip for my friends and I. ...  \n",
       "14    Overview: --Overrated hotel in a premium locat...  \n",
       "15    Not worth the price, even a little bit. A week...  \n",
       "16    I loved this hotel - reasonable for downtown C...  \n",
       "17    I stayed at the Affnia hotel in Chicago and wa...  \n",
       "18    DO NOT STAY AT THIS HOTEL!!!! I would have cer...  \n",
       "19    We stayed for two nights for a meeting. It is ...  \n",
       "20    My husband and I stayed at the Hotel Allegro C...  \n",
       "21    Check-in was fast, the room was perfect, and t...  \n",
       "22    Just returned from the James Hotel after stayi...  \n",
       "23    i was in chicago from september 17-22 for a co...  \n",
       "24    Great hotel in heart of Chicago for business o...  \n",
       "25    I stayed at the Sofitel Chicago Water Tower ho...  \n",
       "26    Three nights there on business. Hadn't realize...  \n",
       "27    The Omni Chicago Hotel is a very high quality ...  \n",
       "28    We booked this trip several months in advance ...  \n",
       "29    My wife and I stayed at the Ambassador East Ho...  \n",
       "...                                                 ...  \n",
       "1250  I stayed at the Fairmont to attend a conferenc...  \n",
       "1251  This is best hotel bargin in Chicago if you ar...  \n",
       "1252  Everything experienced at this hotel was grand...  \n",
       "1253  My wife and I booked a Deluxe Accessible Room ...  \n",
       "1254  ' Barely Average Hotel at Premium Price' This ...  \n",
       "1255  The Affinia is virtually the perfect hotel for...  \n",
       "1256  Spent three nights in Chicago at this property...  \n",
       "1257  The Swissotel Chicago hotel aspires to be a to...  \n",
       "1258  Stayed here for 4 nights in Apri. From check i...  \n",
       "1259  The Affinia hotel in Chicago was superb. the r...  \n",
       "1260  This is a beautiful hotel with a great view of...  \n",
       "1261  The atmosphere at this hotel is truly remarkab...  \n",
       "1262  Good location and looks like a good property b...  \n",
       "1263  My initial thought of the hotel was, this plac...  \n",
       "1264  Our stay at the Ambassador East Hotel was extr...  \n",
       "1265  We got an awesome deal through Priceline for a...  \n",
       "1266  This hotel has a good name and a good location...  \n",
       "1267  This is a great place to stay while visiting C...  \n",
       "1268  We chose the Talbott Hotel primarily for the l...  \n",
       "1269  Great beds, clean rooms, amazing bathroom, nif...  \n",
       "1270  I usually stay at the Hotel Monaco but stayed ...  \n",
       "1271  This hotel is beautiful, it is very modern and...  \n",
       "1272  After some deliberation I booked the Sofitel W...  \n",
       "1273  My wife and I recently stayed at the Allegro h...  \n",
       "1274  My husband and I decided to take a trip to Chi...  \n",
       "1275  Hello, I recently stayed at the Affinia hotel ...  \n",
       "1276  From the moment I stepped up to the front entr...  \n",
       "1277  Just back from a business trip. The Homewood i...  \n",
       "1278  Our first visit to Chicago and I really cannot...  \n",
       "1279  I needed a place to stay for a business confer...  \n",
       "\n",
       "[1280 rows x 6 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "lower_case = letters_only.lower()        # Convert to lower case\n",
    "words = lower_case.split()               # Split into words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I stayed here for a conference and got the conference rate of       I was worried that I wouldn t get a nice room  since it was the weekend before the election and the hotel is across the street from Grant Park  so it could easily have gotten a lot more for the nicer rooms  I requested a quiet room away from elevators and foot traffic  and that is exactly what I was assigned  perhaps because I am also a  silver  member    It was a beautiful room with windows on two sides  a king sized bed  The room was quiet  comfortable and immaculate  The maid even left a thank you note for the tip I had left  All the staff were helpful  polite and cheerful  I appreciated the fact that I could actually purchase a breakfast for under      oatmeal  coffee  and juice   something not possible at a lot of big hotels  like the Hyatt I stayed at last year   \n"
     ]
    }
   ],
   "source": [
    "import re\n",
    "# Use regular expressions to do a find-and-replace\n",
    "letters_only = re.sub(\"[^a-zA-Z]\",           # The pattern to search for\n",
    "                      \" \",                   # The pattern to replace it with\n",
    "                      example1.get_text() )  # The text to search\n",
    "print(letters_only)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "showing info https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/index.xml\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import nltk\n",
    "nltk.download()  # Download text data sets, including stop words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', \"you're\", \"you've\", \"you'll\", \"you'd\", 'your', 'yours', 'yourself', 'yourselves', 'he', 'him', 'his', 'himself', 'she', \"she's\", 'her', 'hers', 'herself', 'it', \"it's\", 'its', 'itself', 'they', 'them', 'their', 'theirs', 'themselves', 'what', 'which', 'who', 'whom', 'this', 'that', \"that'll\", 'these', 'those', 'am', 'is', 'are', 'was', 'were', 'be', 'been', 'being', 'have', 'has', 'had', 'having', 'do', 'does', 'did', 'doing', 'a', 'an', 'the', 'and', 'but', 'if', 'or', 'because', 'as', 'until', 'while', 'of', 'at', 'by', 'for', 'with', 'about', 'against', 'between', 'into', 'through', 'during', 'before', 'after', 'above', 'below', 'to', 'from', 'up', 'down', 'in', 'out', 'on', 'off', 'over', 'under', 'again', 'further', 'then', 'once', 'here', 'there', 'when', 'where', 'why', 'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most', 'other', 'some', 'such', 'no', 'nor', 'not', 'only', 'own', 'same', 'so', 'than', 'too', 'very', 's', 't', 'can', 'will', 'just', 'don', \"don't\", 'should', \"should've\", 'now', 'd', 'll', 'm', 'o', 're', 've', 'y', 'ain', 'aren', \"aren't\", 'couldn', \"couldn't\", 'didn', \"didn't\", 'doesn', \"doesn't\", 'hadn', \"hadn't\", 'hasn', \"hasn't\", 'haven', \"haven't\", 'isn', \"isn't\", 'ma', 'mightn', \"mightn't\", 'mustn', \"mustn't\", 'needn', \"needn't\", 'shan', \"shan't\", 'shouldn', \"shouldn't\", 'wasn', \"wasn't\", 'weren', \"weren't\", 'won', \"won't\", 'wouldn', \"wouldn't\"]\n"
     ]
    }
   ],
   "source": [
    "from nltk.corpus import stopwords # Import the stop word list\n",
    "print(stopwords.words(\"english\")) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['stayed', 'conference', 'got', 'conference', 'rate', 'worried', 'get', 'nice', 'room', 'since', 'weekend', 'election', 'hotel', 'across', 'street', 'grant', 'park', 'could', 'easily', 'gotten', 'lot', 'nicer', 'rooms', 'requested', 'quiet', 'room', 'away', 'elevators', 'foot', 'traffic', 'exactly', 'assigned', 'perhaps', 'also', 'silver', 'member', 'beautiful', 'room', 'windows', 'two', 'sides', 'king', 'sized', 'bed', 'room', 'quiet', 'comfortable', 'immaculate', 'maid', 'even', 'left', 'thank', 'note', 'tip', 'left', 'staff', 'helpful', 'polite', 'cheerful', 'appreciated', 'fact', 'could', 'actually', 'purchase', 'breakfast', 'oatmeal', 'coffee', 'juice', 'something', 'possible', 'lot', 'big', 'hotels', 'like', 'hyatt', 'stayed', 'last', 'year']\n"
     ]
    }
   ],
   "source": [
    "words = [w for w in words if not w in stopwords.words(\"english\")]\n",
    "print(words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def review_to_words( raw_review ):\n",
    "    # Function to convert a raw review to a string of words\n",
    "    # The input is a single string (a raw movie review), and \n",
    "    # the output is a single string (a preprocessed movie review)\n",
    "    #\n",
    "    # 1. Remove HTML\n",
    "    review_text = BeautifulSoup(raw_review).get_text() \n",
    "    #\n",
    "    # 2. Remove non-letters        \n",
    "    letters_only = re.sub(\"[^a-zA-Z]\", \" \", review_text) \n",
    "    #\n",
    "    # 3. Convert to lower case, split into individual words\n",
    "    words = letters_only.lower().split()                             \n",
    "    #\n",
    "    # 4. In Python, searching a set is much faster than searching\n",
    "    #   a list, so convert the stop words to a set\n",
    "    stops = set(stopwords.words(\"english\"))                  \n",
    "    # \n",
    "    # 5. Remove stop words\n",
    "    meaningful_words = [w for w in words if not w in stops]   \n",
    "    #\n",
    "    # 6. Join the words back into one string separated by space, \n",
    "    # and return the result.\n",
    "    return( \" \".join( meaningful_words ))   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "conrad right stuff great bedding fancy decorations beautiful lobby etc however seriously missing boat comes customer service attention detail checked went get glass wine minibar discover everything fridge warm called help cheerfully told would send engineer right away fix meantime said great cold drink proceeded send glass wine via room service without asking would okay paid glass wine minibar bottle would given glasses nothing said obvious difference called complain made feel cheap money principle next morning bill showed eaten something minibar called said automatic sensors minibar must triggered something duh engineer came took entire fridge compartment fix took charge also took room service bill still annoyed nobody bothered apologize acknowledge fact overcharged also fixed minibar fridge replace anything guy said take things cool oh really warm beer cold taste disgusting guess saving next person checks room idea another annoyance lighted mirror bathroom work plugged made lights bathroom go never would come seems conrad thinks spend lot money make look beautiful without worrying customer experience think go rooms check sta\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/bs4/__init__.py:181: UserWarning: No parser was explicitly specified, so I'm using the best available HTML parser for this system (\"lxml\"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently.\n",
      "\n",
      "The code that caused this warning is on line 193 of the file /anaconda3/lib/python3.6/runpy.py. To get rid of this warning, change code that looks like this:\n",
      "\n",
      " BeautifulSoup(YOUR_MARKUP})\n",
      "\n",
      "to this:\n",
      "\n",
      " BeautifulSoup(YOUR_MARKUP, \"lxml\")\n",
      "\n",
      "  markup_type=markup_type))\n"
     ]
    }
   ],
   "source": [
    "clean_review = review_to_words( train[\"text\"].any() )\n",
    "print(clean_review)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/bs4/__init__.py:181: UserWarning: No parser was explicitly specified, so I'm using the best available HTML parser for this system (\"lxml\"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently.\n",
      "\n",
      "The code that caused this warning is on line 193 of the file /anaconda3/lib/python3.6/runpy.py. To get rid of this warning, change code that looks like this:\n",
      "\n",
      " BeautifulSoup(YOUR_MARKUP})\n",
      "\n",
      "to this:\n",
      "\n",
      " BeautifulSoup(YOUR_MARKUP, \"lxml\")\n",
      "\n",
      "  markup_type=markup_type))\n"
     ]
    }
   ],
   "source": [
    "# Get the number of reviews based on the dataframe column size\n",
    "num_reviews = train[\"text\"].size\n",
    "\n",
    "# Initialize an empty list to hold the clean reviews\n",
    "clean_train_reviews = []\n",
    "\n",
    "# Loop over each review; create an index i that goes from 0 to the length\n",
    "# of the movie review list \n",
    "for i in range( 0, num_reviews ):\n",
    "    # Call our function for each one, and add the result to the list of\n",
    "    # clean reviews\n",
    "    clean_train_reviews.append( review_to_words( train[\"text\"][i] ) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating the bag of words...\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"Creating the bag of words...\\n\")\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "\n",
    "# Initialize the \"CountVectorizer\" object, which is scikit-learn's\n",
    "# bag of words tool.  \n",
    "vectorizer = CountVectorizer(analyzer = \"word\",   \\\n",
    "                             tokenizer = None,    \\\n",
    "                             preprocessor = None, \\\n",
    "                             stop_words = None,   \\\n",
    "                             max_features = 5000) \n",
    "\n",
    "# fit_transform() does two functions: First, it fits the model\n",
    "# and learns the vocabulary; second, it transforms our training data\n",
    "# into feature vectors. The input to fit_transform should be a list of \n",
    "# strings.\n",
    "train_data_features = vectorizer.fit_transform(clean_train_reviews)\n",
    "\n",
    "# Numpy arrays are easy to work with, so convert the result to an \n",
    "# array\n",
    "train_data_features = train_data_features.toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1280, 5000)\n"
     ]
    }
   ],
   "source": [
    "print(train_data_features.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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'shows', 'shrugged', 'shuffle', 'shula', 'shut', 'shuttle', 'sick', 'side', 'sides', 'sidewalk', 'sighed', 'sight', 'sights', 'sightseeing', 'sign', 'signal', 'signature', 'signed', 'significant', 'significantly', 'signing', 'signs', 'sill', 'similar', 'similarly', 'simple', 'simply', 'sinatra', 'since', 'sincerely', 'single', 'singles', 'sink', 'sinks', 'sirens', 'sister', 'sisters', 'sit', 'site', 'sites', 'sits', 'sitting', 'situated', 'situation', 'six', 'size', 'sized', 'skeptical', 'skin', 'skip', 'skipped', 'skipping', 'sky', 'skyline', 'slam', 'slammed', 'slap', 'sleek', 'sleep', 'sleeper', 'sleeping', 'sleepless', 'slept', 'slice', 'slide', 'sliding', 'slight', 'slightly', 'slimy', 'slip', 'slippers', 'slippery', 'slipping', 'sliver', 'sloppy', 'slot', 'slow', 'slowed', 'slower', 'slowly', 'slumber', 'slumming', 'smacking', 'small', 'smaller', 'smallest', 'smell', 'smelled', 'smelling', 'smells', 'smelly', 'smile', 'smiles', 'smiling', 'smoke', 'smoked', 'smoker', 'smokers', 'smokey', 'smoking', 'smooth', 'smoothly', 'smudge', 'smudges', 'snack', 'snacking', 'snacks', 'snagged', 'snaps', 'sneak', 'sneek', 'sneezing', 'snickered', 'snickers', 'snide', 'sniping', 'snippets', 'snippy', 'snobbery', 'snobbishness', 'snobby', 'snooping', 'snooty', 'snooze', 'snot', 'snotty', 'snow', 'snubbed', 'snubery', 'snug', 'soak', 'soaking', 'soap', 'soaps', 'social', 'soda', 'sofa', 'sofabed', 'sofas', 'sofitel', 'soft', 'softest', 'softiel', 'software', 'soiled', 'sold', 'soldier', 'solely', 'solid', 'solution', 'somebody', 'somehow', 'someone', 'someplace', 'something', 'sometimes', 'somewhat', 'somewhere', 'son', 'soon', 'sooner', 'soooo', 'soothing', 'sophisticated', 'sophistication', 'sorely', 'sorry', 'sort', 'sorted', 'sorts', 'sound', 'sounded', 'sounding', 'soundly', 'soundproofing', 'sounds', 'soup', 'sour', 'source', 'soured', 'south', 'sox', 'sp', 'spa', 'space', 'spaces', 'spacey', 'spacing', 'spacious', 'spaffina', 'spake', 'spanish', 'spanking', 'spare', 'sparkled', 'sparkling', 'sparsely', 'speak', 'speaker', 'speakers', 'speaking', 'specacular', 'special', 'specialist', 'specially', 'specials', 'specialty', 'specific', 'specifically', 'specifics', 'spectacle', 'spectacular', 'spectacularly', 'speed', 'speeds', 'speedy', 'spell', 'spelled', 'spend', 'spending', 'spends', 'spent', 'spicy', 'spiderwebs', 'spilled', 'spit', 'spite', 'spitting', 'splash', 'splashed', 'splashes', 'splendido', 'splinters', 'split', 'splurge', 'spoil', 'spoiled', 'spoke', 'spoken', 'spolied', 'spontaneous', 'spoon', 'sporting', 'sports', 'spot', 'spotless', 'spotlessly', 'spots', 'spotting', 'spotty', 'sprawled', 'sprawling', 'spray', 'sprayed', 'spread', 'spreading', 'spree', 'spring', 'springs', 'springy', 'spur', 'sq', 'sqft', 'square', 'squeaking', 'squealing', 'squeals', 'squeezed', 'ss', 'st', 'sta', 'stacked', 'stadium', 'staff', 'staffed', 'staffing', 'staffs', 'stage', 'stain', 'stained', 'stainless', 'stains', 'stair', 'staircase', 'stairs', 'stairwell', 'stairwells', 'stale', 'stall', 'stand', 'standard', 'standards', 'standby', 'standing', 'standoffish', 'stands', 'stank', 'star', 'starbucks', 'starched', 'stare', 'stared', 'stares', 'staring', 'stark', 'starpoints', 'stars', 'start', 'started', 'starters', 'starting', 'starts', 'starving', 'starwood', 'stash', 'state', 'stated', 'stately', 'statement', 'states', 'static', 'stating', 'station', 'stations', 'statistical', 'stature', 'stay', 'stayed', 'stayfittm', 'staying', 'stays', 'steady', 'steak', 'steakhouse', 'steaks', 'steal', 'stealing', 'steamer', 'steel', 'steep', 'steer', 'stella', 'stellar', 'step', 'stepdad', 'stephanie', 'stepped', 'steppers', 'stepping', 'steps', 'stereo', 'sterile', 'sterling', 'stetson', 'steven', 'stick', 'stickers', 'stickler', 'sticks', 'sticky', 'stiff', 'stiffness', 'stifling', 'still', 'stinch', 'sting', 'stinking', 'stirrers', 'stock', 'stocked', 'stocking', 'stoked', 'stole', 'stolen', 'stomped', 'stone', 'stood', 'stop', 'stopped', 'stopper', 'stops', 'storage', 'store', 'stores', 'storey', 'storied', 'stories', 'storing', 'storm', 'stormed', 'story', 'stove', 'straight', 'straighten', 'straiten', 'stranded', 'strange', 'strangely', 'strangers', 'strap', 'strawberries', 'stray', 'streaked', 'streamlined', 'street', 'streets', 'streetside', 'strength', 'stress', 'stressed', 'stressful', 'strewn', 'strict', 'strictly', 'strike', 'striking', 'stringers', 'strip', 'striped', 'strives', 'stroll', 'strollers', 'strolling', 'strong', 'strongest', 'strongly', 'structure', 'strudel', 'struggle', 'struggling', 'strut', 'stuck', 'stucture', 'student', 'students', 'studio', 'study', 'stuff', 'stuffed', 'stuffy', 'stumbled', 'stumbling', 'stunned', 'stunning', 'stupid', 'stupidity', 'style', 'styles', 'stylings', 'stylish', 'stylishly', 'styx', 'sub', 'suberb', 'sublime', 'submerge', 'subpar', 'subroofer', 'subsequently', 'substantial', 'subtle', 'suburbs', 'subway', 'success', 'successfully', 'succession', 'succulent', 'sucked', 'suckish', 'sudden', 'suddenly', 'suede', 'suffer', 'suffered', 'suffice', 'sufficient', 'suffocated', 'sugar', 'suggest', 'suggested', 'suggesting', 'suggestion', 'suggestions', 'suit', 'suitcase', 'suitcases', 'suite', 'suited', 'suites', 'suits', 'sulked', 'sullivans', 'sully', 'sum', 'summary', 'summation', 'summed', 'summer', 'summon', 'sun', 'sunday', 'sundecks', 'sunglasses', 'sunlight', 'sunny', 'super', 'superb', 'superbly', 'superficial', 'superior', 'supervisor', 'supper', 'supplied', 'supplies', 'supply', 'support', 'suppose', 'supposed', 'supposedly', 'sure', 'surely', 'surface', 'surgery', 'surly', 'surpassed', 'surprise', 'surprised', 'surprising', 'surprisingly', 'surround', 'surrounded', 'surrounding', 'surveillance', 'sushi', 'suspect', 'sutton', 'suv', 'swear', 'sweat', 'sweet', 'sweets', 'swept', 'swim', 'swimming', 'swisshotel', 'swissotel', 'switch', 'switched', 'sylvia', 'sympathetic', 'sympathy', 'system', 'systems', 'ta', 'table', 'tables', 'tacky', 'tag', 'tainted', 'take', 'taken', 'takes', 'taking', 'talbot', 'talbott', 'talk', 'talked', 'talking', 'tall', 'tank', 'tap', 'target', 'task', 'taste', 'tasted', 'tastefully', 'tasting', 'tasty', 'tattered', 'tax', 'taxes', 'taxi', 'taxis', 'tea', 'team', 'teams', 'tech', 'technical', 'technology', 'teenage', 'teenager', 'teenagers', 'teens', 'television', 'televisions', 'tell', 'telling', 'tells', 'temp', 'temperature', 'tempted', 'ten', 'tend', 'tenth', 'terms', 'terrace', 'terrible', 'terribly', 'terrific', 'terror', 'terry', 'test', 'texting', 'th', 'thank', 'thankfully', 'thanks', 'thanksgiving', 'thats', 'theater', 'theaters', 'theatre', 'theatres', 'theme', 'themed', 'therapy', 'therefore', 'thereof', 'theres', 'thick', 'thier', 'thin', 'thing', 'things', 'think', 'thinking', 'thinks', 'third', 'thirdly', 'thirty', 'thorough', 'thoroughly', 'though', 'thought', 'thread', 'threatened', 'three', 'threw', 'thrilled', 'throbbing', 'throughout', 'throw', 'throwback', 'thrown', 'thru', 'thumbs', 'thursday', 'thus', 'ticket', 'tickets', 'tidy', 'tied', 'til', 'tile', 'tiled', 'tiles', 'till', 'tim', 'time', 'timely', 'times', 'timetable', 'tiny', 'tip', 'tipped', 'tips', 'tired', 'toast', 'today', 'toe', 'together', 'toilet', 'toiletries', 'told', 'tolerable', 'tolerate', 'toliet', 'tomato', 'ton', 'tone', 'tones', 'toni', 'tons', 'took', 'tools', 'toothpaste', 'top', 'topped', 'tops', 'torn', 'tossed', 'total', 'totally', 'touch', 'touched', 'touches', 'tough', 'tour', 'touring', 'tourist', 'tourists', 'touristy', 'tours', 'touted', 'toward', 'towards', 'towel', 'towels', 'tower', 'towering', 'towers', 'town', 'towners', 'track', 'trade', 'trader', 'traditional', 'traffic', 'train', 'trained', 'training', 'trains', 'traits', 'tranquility', 'transfer', 'transferred', 'transit', 'transport', 'transportation', 'trash', 'travel', 'traveled', 'traveler', 'travelers', 'traveling', 'travelled', 'traveller', 'travellers', 'travelling', 'travels', 'travelzoo', 'tray', 'trays', 'treadmill', 'treadmills', 'treasure', 'treat', 'treated', 'treating', 'treatment', 'treatments', 'treats', 'tree', 'tremendous', 'trendy', 'tribune', 'trickle', 'tried', 'tries', 'trip', 'tripadvisor', 'triple', 'trips', 'trolley', 'trouble', 'troubles', 'truck', 'trucks', 'true', 'truely', 'truly', 'trump', 'trust', 'truth', 'try', 'trying', 'tub', 'tubs', 'tucked', 'tuesday', 'turd', 'turn', 'turndown', 'turned', 'turning', 'turns', 'tv', 'tvs', 'twelveth', 'twenty', 'twice', 'twin', 'two', 'type', 'types', 'typical', 'typically', 'typing', 'ugh', 'ugly', 'uk', 'ultimate', 'ultimately', 'ultra', 'umbrella', 'unable', 'unacceptable', 'unaccomodating', 'unavailable', 'unaware', 'unbeatable', 'unbelievable', 'unbelievably', 'uncaring', 'unclean', 'uncomfortable', 'uncomfortably', 'undergoing', 'underground', 'underneath', 'understaffed', 'understand', 'understatement', 'underwhelming', 'unexpected', 'unfailingly', 'unfinished', 'unfortunate', 'unfortunately', 'unfriendly', 'unhappy', 'unhelpful', 'uniform', 'uniformly', 'unimpressed', 'unimpressive', 'uninspired', 'uninterested', 'uninviting', 'unique', 'unit', 'united', 'unless', 'unlike', 'unload', 'unmade', 'unpacking', 'unpleasant', 'unprofessional', 'unreasonable', 'unresponsive', 'unsanitary', 'unsatisfactory', 'unsatisfied', 'untill', 'unusual', 'unusually', 'unwelcome', 'unwilling', 'unwind', 'upbeat', 'upcharge', 'upcoming', 'update', 'updated', 'updating', 'upgrade', 'upgraded', 'upgrades', 'upgrading', 'upholstered', 'upon', 'upper', 'ups', 'upscale', 'upset', 'upstairs', 'urban', 'urine', 'us', 'usa', 'usage', 'usd', 'use', 'used', 'user', 'uses', 'using', 'usual', 'usually', 'utilize', 'utilized', 'utmost', 'vacant', 'vacation', 'vacuum', 'vacuumed', 'valet', 'valets', 'valuables', 'value', 'valued', 'van', 'vanity', 'variety', 'various', 'vegas', 'vehicle', 'vending', 'vent', 'venting', 'vents', 'venue', 'verify', 'versed', 'via', 'vibe', 'vicinity', 'victor', 'victorian', 'video', 'view', 'viewing', 'views', 'virtually', 'visible', 'visit', 'visited', 'visiting', 'visitor', 'visitors', 'visits', 'voice', 'voiced', 'voices', 'volume', 'vomit', 'voucher', 'vouchers', 'vs', 'wacker', 'waffle', 'wait', 'waited', 'waiter', 'waiters', 'waiting', 'waitress', 'waits', 'waived', 'wake', 'wakeup', 'waking', 'walk', 'walkable', 'walked', 'walking', 'wall', 'wallet', 'wallpaper', 'walls', 'wander', 'want', 'wanted', 'wanting', 'wants', 'warm', 'warmer', 'warmly', 'warmth', 'warned', 'warning', 'wash', 'washed', 'washington', 'washroom', 'wasnt', 'waste', 'wastebasket', 'watch', 'watched', 'watching', 'water', 'waterfront', 'way', 'ways', 'weak', 'wear', 'wearing', 'weather', 'web', 'website', 'websites', 'wedding', 'weddings', 'wednesday', 'wee', 'week', 'weekend', 'weekends', 'weeks', 'weight', 'weights', 'weird', 'welcome', 'welcomed', 'welcoming', 'well', 'went', 'west', 'western', 'westin', 'wet', 'whatever', 'whatsoever', 'wheelchair', 'whenever', 'whether', 'whilst', 'whim', 'whistle', 'whistled', 'white', 'whole', 'wi', 'wicked', 'wide', 'wife', 'wifi', 'willing', 'wind', 'window', 'windows', 'windy', 'wine', 'wines', 'winning', 'winter', 'wire', 'wired', 'wireless', 'wise', 'wish', 'wished', 'wishing', 'within', 'without', 'witnessed', 'woefully', 'woke', 'woken', 'woman', 'women', 'wonder', 'wonderful', 'wonderfull', 'wonderfully', 'wondering', 'wont', 'wood', 'wooden', 'word', 'words', 'work', 'worked', 'worker', 'workers', 'working', 'workout', 'works', 'world', 'worn', 'worried', 'worry', 'worrying', 'worse', 'worst', 'worth', 'worthy', 'woudl', 'would', 'wouldnt', 'wow', 'wowed', 'wrap', 'wrapped', 'wrigley', 'wrinkled', 'write', 'writing', 'written', 'wrong', 'wrote', 'yeah', 'year', 'yearly', 'years', 'yelling', 'yellow', 'yelp', 'yep', 'yes', 'yesterday', 'yet', 'yoga', 'yogurt', 'york', 'young', 'younger', 'youve', 'yuck', 'yummy', 'zest', 'zone', 'zoo']\n"
     ]
    }
   ],
   "source": [
    "# Take a look at the words in the vocabulary\n",
    "vocab = vectorizer.get_feature_names()\n",
    "print(vocab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6 aaa\n",
      "2 abassador\n",
      "5 ability\n",
      "97 able\n",
      "2 absence\n",
      "6 absolute\n",
      "68 absolutely\n",
      "2 abundant\n",
      "2 abysmal\n",
      "5 ac\n",
      "2 accent\n",
      "4 accept\n",
      "5 acceptable\n",
      "9 accepted\n",
      "2 accepting\n",
      "67 access\n",
      "8 accessible\n",
      "2 accidentally\n",
      "2 accomidations\n",
      "11 accommodate\n",
      "2 accommodated\n",
      "19 accommodating\n",
      "46 accommodations\n",
      "4 accomodate\n",
      "9 accomodating\n",
      "5 accomodations\n",
      "4 accompanied\n",
      "2 according\n",
      "21 account\n",
      "2 accounting\n",
      "2 accounts\n",
      "3 accurate\n",
      "2 accused\n",
      "2 ache\n",
      "6 acknowledge\n",
      "9 acknowledged\n",
      "2 acne\n",
      "37 across\n",
      "3 act\n",
      "11 acted\n",
      "5 action\n",
      "2 activate\n",
      "8 activities\n",
      "13 actual\n",
      "73 actually\n",
      "13 add\n",
      "18 added\n",
      "18 addition\n",
      "23 additional\n",
      "7 additionally\n",
      "4 address\n",
      "2 addressed\n",
      "12 adequate\n",
      "14 adjacent\n",
      "7 adjoining\n",
      "2 adjust\n",
      "2 adjustment\n",
      "2 admired\n",
      "4 admit\n",
      "2 admitted\n",
      "2 admittedly\n",
      "2 adored\n",
      "4 adult\n",
      "10 adults\n",
      "15 advance\n",
      "13 advantage\n",
      "2 adventure\n",
      "4 advertise\n",
      "20 advertised\n",
      "5 advertises\n",
      "3 advertising\n",
      "2 advertized\n",
      "5 advice\n",
      "6 advise\n",
      "5 advised\n",
      "9 advisor\n",
      "3 ae\n",
      "3 aesthetic\n",
      "2 affair\n",
      "7 affina\n",
      "47 affinia\n",
      "2 affluent\n",
      "3 afford\n",
      "2 affordability\n",
      "10 affordable\n",
      "2 aforementioned\n",
      "3 afraid\n",
      "23 afternoon\n",
      "2 afterward\n",
      "4 afterwards\n",
      "3 age\n",
      "2 aged\n",
      "6 agent\n",
      "3 ages\n",
      "4 aggravating\n",
      "29 ago\n",
      "6 agree\n",
      "11 agreed\n",
      "2 agreement\n",
      "14 ahead\n",
      "3 aid\n",
      "65 air\n",
      "6 airline\n",
      "3 airlines\n",
      "26 airport\n",
      "2 airshow\n",
      "3 airy\n",
      "2 aka\n",
      "7 alarm\n",
      "3 alas\n",
      "3 albeit\n",
      "2 alcove\n",
      "69 allegro\n",
      "5 allergenic\n",
      "3 allergic\n",
      "7 allergies\n",
      "7 allergy\n",
      "6 alley\n",
      "15 allow\n",
      "20 allowed\n",
      "6 allowing\n",
      "6 allows\n",
      "2 alludes\n",
      "71 almost\n",
      "15 alone\n",
      "31 along\n",
      "2 aloof\n",
      "6 alot\n",
      "49 already\n",
      "8 alright\n",
      "327 also\n",
      "3 alternative\n",
      "2 alternatives\n",
      "85 although\n",
      "3 altogether\n",
      "94 always\n",
      "60 amalfi\n",
      "2 amateur\n",
      "10 amazed\n",
      "101 amazing\n",
      "8 amazingly\n",
      "74 ambassador\n",
      "11 ambiance\n",
      "4 ambience\n",
      "3 ambulance\n",
      "91 amenities\n",
      "8 amenity\n",
      "2 america\n",
      "20 american\n",
      "3 ammenities\n",
      "7 among\n",
      "29 amount\n",
      "2 amounts\n",
      "4 ample\n",
      "2 andrew\n",
      "2 ands\n",
      "2 angie\n",
      "4 angry\n",
      "3 animal\n",
      "3 animals\n",
      "48 anniversary\n",
      "3 annoyance\n",
      "12 annoyed\n",
      "16 annoying\n",
      "2 annual\n",
      "166 another\n",
      "11 answer\n",
      "18 answered\n",
      "3 answers\n",
      "5 anthony\n",
      "4 anticipated\n",
      "2 ants\n",
      "4 anxious\n",
      "5 anybody\n",
      "9 anymore\n",
      "101 anyone\n",
      "3 anyplace\n",
      "81 anything\n",
      "15 anytime\n",
      "21 anyway\n",
      "2 anyways\n",
      "25 anywhere\n",
      "2 aon\n",
      "9 apart\n",
      "8 apartment\n",
      "5 apologetic\n",
      "7 apologies\n",
      "9 apologize\n",
      "8 apologized\n",
      "17 apology\n",
      "6 appalled\n",
      "2 apparent\n",
      "22 apparently\n",
      "3 appealing\n",
      "6 appear\n",
      "5 appearance\n",
      "2 appearances\n",
      "24 appeared\n",
      "5 appears\n",
      "10 appetizers\n",
      "3 apple\n",
      "3 appliances\n",
      "2 applies\n",
      "2 apply\n",
      "26 appointed\n",
      "2 appointment\n",
      "8 appreciate\n",
      "13 appreciated\n",
      "2 apprehensive\n",
      "4 approach\n",
      "6 approached\n",
      "2 approched\n",
      "2 approx\n",
      "2 approximately\n",
      "5 april\n",
      "11 aquarium\n",
      "5 architectes\n",
      "9 architecture\n",
      "195 area\n",
      "35 areas\n",
      "6 argue\n",
      "5 argued\n",
      "4 arguing\n",
      "9 aria\n",
      "6 arm\n",
      "2 arose\n",
      "140 around\n",
      "2 arrange\n",
      "14 arranged\n",
      "5 arrangements\n",
      "4 array\n",
      "51 arrival\n",
      "22 arrive\n",
      "184 arrived\n",
      "23 arriving\n",
      "4 arrogant\n",
      "37 art\n",
      "2 articles\n",
      "2 artistic\n",
      "5 artwork\n",
      "2 asap\n",
      "3 asha\n",
      "3 ashamed\n",
      "3 ashtray\n",
      "3 asian\n",
      "7 aside\n",
      "60 ask\n",
      "165 asked\n",
      "24 asking\n",
      "4 asleep\n",
      "5 aspect\n",
      "4 aspects\n",
      "2 aspires\n",
      "11 assigned\n",
      "5 assist\n",
      "6 assistance\n",
      "6 assistant\n",
      "3 assisted\n",
      "3 assisting\n",
      "3 associate\n",
      "3 associates\n",
      "8 assume\n",
      "5 assumed\n",
      "2 assuming\n",
      "18 assured\n",
      "2 asthma\n",
      "2 asthmatic\n",
      "24 ate\n",
      "2 atlanta\n",
      "2 atlantic\n",
      "41 atmosphere\n",
      "2 atop\n",
      "2 atrium\n",
      "2 atrocious\n",
      "14 attached\n",
      "2 attacked\n",
      "3 attacks\n",
      "5 attempt\n",
      "7 attempted\n",
      "2 attempting\n",
      "4 attempts\n",
      "12 attend\n",
      "7 attendant\n",
      "2 attendants\n",
      "11 attended\n",
      "2 attendees\n",
      "12 attending\n",
      "21 attention\n",
      "21 attentive\n",
      "3 attentiveness\n",
      "2 attic\n",
      "20 attitude\n",
      "3 attracted\n",
      "39 attractions\n",
      "10 attractive\n",
      "2 audible\n",
      "2 aug\n",
      "8 august\n",
      "3 authorization\n",
      "4 automatically\n",
      "3 av\n",
      "3 availability\n",
      "103 available\n",
      "65 ave\n",
      "8 aveda\n",
      "48 avenue\n",
      "33 average\n",
      "26 avoid\n",
      "5 avoided\n",
      "2 avoiding\n",
      "2 awaiting\n",
      "7 awake\n",
      "3 awaken\n",
      "2 awakened\n",
      "2 awakening\n",
      "5 award\n",
      "9 aware\n",
      "150 away\n",
      "24 awesome\n",
      "22 awful\n",
      "5 awhile\n",
      "3 awkward\n",
      "6 awoke\n",
      "3 babies\n",
      "7 baby\n",
      "314 back\n",
      "2 backdrop\n",
      "3 background\n",
      "2 backpack\n",
      "3 bacon\n",
      "110 bad\n",
      "3 badly\n",
      "2 baffled\n",
      "8 bag\n",
      "2 bagel\n",
      "4 bagels\n",
      "5 baggage\n",
      "43 bags\n",
      "3 bakery\n",
      "4 ball\n",
      "6 ballroom\n",
      "2 ballrooms\n",
      "2 balls\n",
      "7 band\n",
      "2 bang\n",
      "4 banging\n",
      "8 bank\n",
      "181 bar\n",
      "2 bare\n",
      "21 barely\n",
      "8 bargain\n",
      "2 bargains\n",
      "6 barking\n",
      "2 barman\n",
      "2 barrier\n",
      "25 bars\n",
      "9 bartender\n",
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      "9 base\n",
      "22 based\n",
      "6 basement\n",
      "12 basic\n",
      "16 basically\n",
      "3 basics\n",
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      "2 basket\n",
      "2 bass\n",
      "2 bat\n",
      "29 bath\n",
      "9 bathrobes\n",
      "277 bathroom\n",
      "35 bathrooms\n",
      "4 baths\n",
      "8 bathtub\n",
      "2 battery\n",
      "7 beach\n",
      "4 bears\n",
      "20 beat\n",
      "3 beatles\n",
      "2 beats\n",
      "164 beautiful\n",
      "2 beautifull\n",
      "19 beautifully\n",
      "6 beauty\n",
      "5 became\n",
      "3 become\n",
      "3 becuase\n",
      "336 bed\n",
      "5 bedbugs\n",
      "28 bedding\n",
      "30 bedroom\n",
      "4 bedrooms\n",
      "144 beds\n",
      "3 bedsheets\n",
      "3 bedside\n",
      "2 bedspreads\n",
      "2 beep\n",
      "18 beer\n",
      "2 beforehand\n",
      "14 began\n",
      "9 begin\n",
      "9 beginning\n",
      "29 behind\n",
      "2 behold\n",
      "43 believe\n",
      "2 believed\n",
      "27 bell\n",
      "5 bellboy\n",
      "7 bellhop\n",
      "12 bellman\n",
      "6 bellmen\n",
      "3 belongings\n",
      "2 beneath\n",
      "2 benedict\n",
      "2 benefit\n",
      "3 benefits\n",
      "3 bent\n",
      "5 besides\n",
      "190 best\n",
      "2 betsy\n",
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      "3 beverage\n",
      "7 beverages\n",
      "8 beware\n",
      "25 beyond\n",
      "2 bfast\n",
      "2 bid\n",
      "84 big\n",
      "7 bigger\n",
      "7 biggest\n",
      "31 bill\n",
      "5 billed\n",
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      "2 billy\n",
      "4 bin\n",
      "2 birdland\n",
      "8 birthday\n",
      "2 biscuits\n",
      "2 bistro\n",
      "97 bit\n",
      "6 bites\n",
      "3 bitten\n",
      "7 black\n",
      "2 blackout\n",
      "3 blamed\n",
      "6 bland\n",
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      "12 blankets\n",
      "2 bldg\n",
      "2 blender\n",
      "7 blew\n",
      "30 block\n",
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      "2 blond\n",
      "8 blood\n",
      "5 bloomingdales\n",
      "2 blow\n",
      "6 blowing\n",
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      "6 blue\n",
      "5 blues\n",
      "5 board\n",
      "5 boarding\n",
      "3 boards\n",
      "2 boasted\n",
      "3 boasts\n",
      "2 boat\n",
      "9 body\n",
      "2 bolted\n",
      "10 bonus\n",
      "2 bonuses\n",
      "51 book\n",
      "169 booked\n",
      "23 booking\n",
      "5 bored\n",
      "5 boring\n",
      "2 borrow\n",
      "5 bose\n",
      "14 bother\n",
      "8 bothered\n",
      "3 bothering\n",
      "23 bottle\n",
      "6 bottled\n",
      "12 bottles\n",
      "12 bottom\n",
      "4 bought\n",
      "21 boutique\n",
      "4 boutiques\n",
      "8 bowl\n",
      "3 box\n",
      "17 boy\n",
      "7 boyfriend\n",
      "3 boys\n",
      "14 brand\n",
      "2 brands\n",
      "3 bread\n",
      "4 breads\n",
      "17 break\n",
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      "7 breakfasts\n",
      "2 breaking\n",
      "9 breath\n",
      "15 breathtaking\n",
      "2 breathtakingly\n",
      "6 breeze\n",
      "10 brick\n",
      "3 bridge\n",
      "4 brief\n",
      "2 briefcase\n",
      "13 bright\n",
      "42 bring\n",
      "8 bringing\n",
      "2 brings\n",
      "2 british\n",
      "2 brochure\n",
      "2 brochures\n",
      "6 broke\n",
      "39 broken\n",
      "7 brother\n",
      "42 brought\n",
      "14 brown\n",
      "5 brunch\n",
      "4 btw\n",
      "2 bubbles\n",
      "4 buck\n",
      "4 bucket\n",
      "3 buckingham\n",
      "9 bucks\n",
      "2 bud\n",
      "2 buddy\n",
      "2 budge\n",
      "12 budget\n",
      "35 buffet\n",
      "11 bug\n",
      "14 bugs\n",
      "60 building\n",
      "4 buildings\n",
      "8 built\n",
      "4 bulb\n",
      "2 bummed\n",
      "2 bumper\n",
      "3 bumping\n",
      "2 bumps\n",
      "8 bunch\n",
      "2 bunny\n",
      "6 burger\n",
      "2 burgers\n",
      "5 burke\n",
      "4 burnham\n",
      "3 burns\n",
      "5 burnt\n",
      "14 bus\n",
      "4 buses\n",
      "235 business\n",
      "2 bust\n",
      "4 bustle\n",
      "38 busy\n",
      "3 butter\n",
      "4 button\n",
      "7 buy\n",
      "37 cab\n",
      "6 cabinet\n",
      "8 cable\n",
      "7 cabs\n",
      "19 cafe\n",
      "11 cake\n",
      "2 cakes\n",
      "4 caliber\n",
      "4 california\n",
      "109 call\n",
      "189 called\n",
      "16 calling\n",
      "25 calls\n",
      "3 cam\n",
      "134 came\n",
      "2 camera\n",
      "7 cancel\n",
      "6 canceled\n",
      "5 cancellation\n",
      "4 cancelled\n",
      "4 candles\n",
      "2 cane\n",
      "24 cannot\n",
      "2 cant\n",
      "1 canted\n",
      "5 cap\n",
      "1 capable\n",
      "1 capacity\n",
      "1 caps\n",
      "1 captured\n",
      "70 car\n",
      "1 caravan\n",
      "2 caray\n",
      "1 carbide\n",
      "1 carbon\n",
      "70 card\n",
      "1 cardboard\n",
      "6 cardio\n",
      "12 cards\n",
      "45 care\n",
      "6 cared\n",
      "4 careful\n",
      "2 carefully\n",
      "2 cares\n",
      "1 caribbean\n",
      "5 caring\n",
      "2 carlton\n",
      "1 carmines\n",
      "1 carolina\n",
      "1 caroline\n",
      "1 carousing\n",
      "51 carpet\n",
      "1 carpeted\n",
      "5 carpeting\n",
      "11 carpets\n",
      "1 carriage\n",
      "4 carried\n",
      "1 carrot\n",
      "13 carry\n",
      "2 carrying\n",
      "2 cars\n",
      "6 cart\n",
      "1 carte\n",
      "25 case\n",
      "3 cases\n",
      "1 casey\n",
      "6 cash\n",
      "2 cast\n",
      "2 castle\n",
      "1 casts\n",
      "1 casual\n",
      "1 casually\n",
      "2 cat\n",
      "1 catalogue\n",
      "6 catch\n",
      "1 catches\n",
      "2 catching\n",
      "1 category\n",
      "3 cater\n",
      "4 catered\n",
      "3 catering\n",
      "3 caters\n",
      "4 caught\n",
      "6 cause\n",
      "7 caused\n",
      "1 causing\n",
      "1 caution\n",
      "1 cavalier\n",
      "1 cavernous\n",
      "11 cd\n",
      "1 cds\n",
      "1 cece\n",
      "9 ceiling\n",
      "5 ceilings\n",
      "9 celebrate\n",
      "1 celebrated\n",
      "2 celebrating\n",
      "1 celebration\n",
      "2 celebrities\n",
      "3 celebrity\n",
      "10 cell\n",
      "1 cellar\n",
      "2 cellphone\n",
      "1 cells\n",
      "1 cent\n",
      "80 center\n",
      "2 centers\n",
      "12 central\n",
      "1 centralized\n",
      "10 centrally\n",
      "10 centre\n",
      "1 centric\n",
      "3 cents\n",
      "5 century\n",
      "1 ceo\n",
      "3 cereal\n",
      "1 cereals\n",
      "2 ceremony\n",
      "11 certain\n",
      "37 certainly\n",
      "5 certificate\n",
      "1 chacago\n",
      "1 chad\n",
      "1 chagall\n",
      "1 chage\n",
      "2 chagrin\n",
      "22 chain\n",
      "3 chains\n",
      "26 chair\n",
      "13 chairs\n",
      "1 chaise\n",
      "1 challenge\n",
      "1 challenged\n",
      "1 chamber\n",
      "1 chambermaid\n",
      "10 champagne\n",
      "1 champane\n",
      "18 chance\n",
      "1 chances\n",
      "33 change\n",
      "30 changed\n",
      "3 changes\n",
      "7 changing\n",
      "6 channel\n",
      "9 channels\n",
      "1 chaotic\n",
      "1 chaperones\n",
      "2 chapter\n",
      "3 character\n",
      "1 characters\n",
      "72 charge\n",
      "45 charged\n",
      "23 charges\n",
      "12 charging\n",
      "1 charities\n",
      "1 charity\n",
      "2 charlie\n",
      "17 charm\n",
      "7 charming\n",
      "2 chat\n",
      "1 chatted\n",
      "2 chatting\n",
      "35 cheap\n",
      "8 cheaper\n",
      "7 cheapest\n",
      "2 cheaply\n",
      "1 chechecked\n",
      "300 check\n",
      "147 checked\n",
      "6 checkin\n",
      "58 checking\n",
      "1 checklist\n",
      "17 checkout\n",
      "3 checks\n",
      "5 cheerful\n",
      "2 cheerfully\n",
      "1 cheering\n",
      "14 cheese\n",
      "3 cheesecake\n",
      "3 cheeses\n",
      "3 cheesy\n",
      "4 chef\n",
      "1 chefs\n",
      "1 chemical\n",
      "2 chemicals\n",
      "2 cherry\n",
      "1 cheryl\n",
      "3 chestnut\n",
      "1 chew\n",
      "1 chewed\n",
      "2 chewing\n",
      "7 chi\n",
      "17 chic\n",
      "1228 chicago\n",
      "1 chicagoan\n",
      "1 chicagoland\n",
      "1 chichi\n",
      "5 chicken\n",
      "1 chicqgo\n",
      "1 chief\n",
      "1 chigaco\n",
      "1 chihuahua\n",
      "9 child\n",
      "31 children\n",
      "1 chill\n",
      "4 chilled\n",
      "2 chillout\n",
      "2 china\n",
      "4 chinese\n",
      "1 chintzy\n",
      "4 chipped\n",
      "2 chips\n",
      "1 chlorine\n",
      "16 chocolate\n",
      "2 chocolates\n",
      "51 choice\n",
      "10 choices\n",
      "1 choking\n",
      "34 choose\n",
      "7 choosing\n",
      "3 chop\n",
      "1 chopped\n",
      "1 chops\n",
      "1 chores\n",
      "42 chose\n",
      "7 chosen\n",
      "1 chris\n",
      "1 chriskindl\n",
      "1 christening\n",
      "5 christmas\n",
      "3 christopher\n",
      "2 christy\n",
      "1 chronological\n",
      "1 chuckled\n",
      "2 church\n",
      "3 cider\n",
      "1 cig\n",
      "1 cigar\n",
      "14 cigarette\n",
      "6 cigarettes\n",
      "1 cigarrettes\n",
      "1 cinch\n",
      "2 cinema\n",
      "1 circa\n",
      "1 circulation\n",
      "1 circumstance\n",
      "3 circumstances\n",
      "9 cities\n",
      "209 city\n",
      "1 civilised\n",
      "10 claim\n",
      "6 claimed\n",
      "1 claiming\n",
      "8 claims\n",
      "4 clark\n",
      "1 clashing\n",
      "33 class\n",
      "1 classed\n",
      "1 classes\n",
      "13 classic\n",
      "3 classical\n",
      "1 classically\n",
      "1 classier\n",
      "1 classified\n",
      "21 classy\n",
      "2 claustrophobic\n",
      "1 claw\n",
      "341 clean\n",
      "56 cleaned\n",
      "4 cleaner\n",
      "3 cleaners\n",
      "5 cleanest\n",
      "1 cleanin\n",
      "49 cleaning\n",
      "20 cleanliness\n",
      "1 cleanly\n",
      "7 clear\n",
      "2 cleared\n",
      "25 clearly\n",
      "1 cleaver\n",
      "71 clerk\n",
      "5 clerks\n",
      "1 cleveland\n",
      "1 cleverly\n",
      "2 cliche\n",
      "2 click\n",
      "1 clicked\n",
      "7 client\n",
      "1 clientel\n",
      "3 clientele\n",
      "8 clients\n",
      "1 cliff\n",
      "2 climate\n",
      "3 clinical\n",
      "2 clip\n",
      "5 clock\n",
      "1 clocks\n",
      "3 clogged\n",
      "114 close\n",
      "25 closed\n",
      "1 closeout\n",
      "10 closer\n",
      "5 closes\n",
      "3 closest\n",
      "32 closet\n",
      "5 closets\n",
      "2 closing\n",
      "3 cloth\n",
      "13 clothes\n",
      "3 clothing\n",
      "2 cloths\n",
      "5 cloud\n",
      "1 cloying\n",
      "35 club\n",
      "1 clubing\n",
      "8 clubs\n",
      "2 clue\n",
      "1 cluelessness\n",
      "1 clump\n",
      "1 clunked\n",
      "4 co\n",
      "12 coast\n",
      "1 coastal\n",
      "2 coat\n",
      "4 cockroach\n",
      "1 cockroaches\n",
      "12 cocktail\n",
      "8 cocktails\n",
      "3 code\n",
      "1 cofee\n",
      "1 coffe\n",
      "105 coffee\n",
      "4 coffeemaker\n",
      "2 coffees\n",
      "1 coffer\n",
      "1 coincierge\n",
      "1 colada\n",
      "67 cold\n",
      "1 colder\n",
      "1 coleman\n",
      "1 collapsing\n",
      "1 colleague\n",
      "3 colleagues\n",
      "2 collect\n",
      "3 collected\n",
      "4 collection\n",
      "1 colleen\n",
      "10 college\n",
      "1 colleges\n",
      "8 color\n",
      "1 colored\n",
      "9 colors\n",
      "9 com\n",
      "5 combination\n",
      "2 combine\n",
      "2 combined\n",
      "94 come\n",
      "17 comes\n",
      "27 comfort\n",
      "236 comfortable\n",
      "7 comfortably\n",
      "10 comforter\n",
      "4 comforting\n",
      "2 comforts\n",
      "29 comfy\n",
      "51 coming\n",
      "9 comment\n",
      "2 commented\n",
      "7 comments\n",
      "7 common\n",
      "2 communication\n",
      "4 comp\n",
      "30 company\n",
      "4 comparable\n",
      "3 compare\n",
      "15 compared\n",
      "4 comparison\n",
      "4 compelled\n",
      "8 compensate\n",
      "9 compensation\n",
      "5 competent\n",
      "2 competition\n",
      "35 complain\n",
      "28 complained\n",
      "11 complaining\n",
      "1 complains\n",
      "22 complaint\n",
      "21 complaints\n",
      "1 complemenatry\n",
      "8 complementary\n",
      "21 complete\n",
      "2 completed\n",
      "41 completely\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2 completing\n",
      "1 complex\n",
      "2 complicated\n",
      "1 compliment\n",
      "1 complimentarily\n",
      "63 complimentary\n",
      "1 complimented\n",
      "3 compliments\n",
      "1 comprehensive\n",
      "1 compressor\n",
      "1 compromise\n",
      "26 computer\n",
      "10 computers\n",
      "2 conceirge\n",
      "3 concept\n",
      "9 concern\n",
      "5 concerned\n",
      "2 concerns\n",
      "6 concert\n",
      "105 concierge\n",
      "3 concierges\n",
      "2 concluded\n",
      "2 concourse\n",
      "5 concrete\n",
      "4 condescending\n",
      "10 condition\n",
      "14 conditioner\n",
      "12 conditioning\n",
      "4 conditions\n",
      "1 condominiums\n",
      "3 condos\n",
      "3 conducive\n",
      "2 conduct\n",
      "1 conducted\n",
      "1 conducting\n",
      "73 conference\n",
      "6 conferences\n",
      "2 confidence\n",
      "2 confident\n",
      "1 configerations\n",
      "2 configured\n",
      "9 confirm\n",
      "22 confirmation\n",
      "8 confirmed\n",
      "2 confirming\n",
      "2 confronted\n",
      "5 confused\n",
      "2 confusing\n",
      "2 confusion\n",
      "6 connect\n",
      "8 connected\n",
      "2 connecting\n",
      "11 connection\n",
      "3 connections\n",
      "2 connectivity\n",
      "68 conrad\n",
      "9 cons\n",
      "2 consecutive\n",
      "2 consequently\n",
      "10 consider\n",
      "3 consideration\n",
      "11 considered\n",
      "24 considering\n",
      "4 consierge\n",
      "3 consisted\n",
      "2 consistent\n",
      "4 consistently\n",
      "9 constant\n",
      "7 constantly\n",
      "47 construction\n",
      "2 consumer\n",
      "15 contact\n",
      "6 contacted\n",
      "3 contacting\n",
      "2 contain\n",
      "2 contemplated\n",
      "8 contemporary\n",
      "2 content\n",
      "18 continental\n",
      "9 continue\n",
      "12 continued\n",
      "2 contract\n",
      "2 contrary\n",
      "2 contributed\n",
      "15 control\n",
      "3 controls\n",
      "6 convenience\n",
      "40 convenient\n",
      "23 conveniently\n",
      "24 convention\n",
      "6 conversation\n",
      "6 conversations\n",
      "2 converted\n",
      "2 convince\n",
      "7 convinced\n",
      "5 cook\n",
      "7 cooked\n",
      "3 cookie\n",
      "6 cookies\n",
      "3 cooking\n",
      "41 cool\n",
      "2 cooled\n",
      "2 cooler\n",
      "3 coolest\n",
      "3 cooling\n",
      "2 coordinate\n",
      "2 copies\n",
      "6 copy\n",
      "2 cordial\n",
      "51 corner\n",
      "4 corners\n",
      "20 corporate\n",
      "13 correct\n",
      "7 corrected\n",
      "1 correction\n",
      "6 correctly\n",
      "3 corridor\n",
      "1 corridors\n",
      "1 corteous\n",
      "46 cost\n",
      "1 costing\n",
      "14 costs\n",
      "1 cosy\n",
      "3 cot\n",
      "1 cotails\n",
      "2 cotton\n",
      "15 couch\n",
      "2 couches\n",
      "1 cough\n",
      "366 could\n",
      "1 couldin\n",
      "2 couldnt\n",
      "4 count\n",
      "3 counted\n",
      "26 counter\n",
      "1 counterspace\n",
      "2 countertops\n",
      "1 countless\n",
      "4 country\n",
      "46 couple\n",
      "1 coupled\n",
      "4 couples\n",
      "1 coupon\n",
      "27 course\n",
      "2 court\n",
      "28 courteous\n",
      "1 courteously\n",
      "1 courtesty\n",
      "4 courtesy\n",
      "1 courtiest\n",
      "2 courtyard\n",
      "1 cousin\n",
      "1 cousins\n",
      "13 cover\n",
      "16 covered\n",
      "3 covering\n",
      "5 covers\n",
      "1 coworker\n",
      "32 cozy\n",
      "1 cpap\n",
      "1 crabtree\n",
      "4 cracked\n",
      "1 crackle\n",
      "1 crackling\n",
      "1 cracks\n",
      "1 crafted\n",
      "1 craig\n",
      "1 cram\n",
      "2 cramp\n",
      "12 cramped\n",
      "1 cranked\n",
      "2 cranky\n",
      "1 crap\n",
      "6 crappy\n",
      "1 crash\n",
      "1 crashed\n",
      "1 craw\n",
      "2 crawling\n",
      "7 crazy\n",
      "5 cream\n",
      "1 creams\n",
      "2 create\n",
      "1 created\n",
      "2 creates\n",
      "4 creating\n",
      "1 creatively\n",
      "1 credentials\n",
      "46 credit\n",
      "2 credited\n",
      "4 credits\n",
      "1 creepy\n",
      "2 crepes\n",
      "5 crew\n",
      "3 crib\n",
      "1 cried\n",
      "1 crim\n",
      "1 crip\n",
      "1 cripped\n",
      "3 crisp\n",
      "2 crisps\n",
      "1 crispy\n",
      "1 critical\n",
      "1 criticize\n",
      "1 critters\n",
      "1 croissant\n",
      "2 croissants\n",
      "2 cross\n",
      "1 crossed\n",
      "6 crowd\n",
      "14 crowded\n",
      "4 crowds\n",
      "1 crowed\n",
      "1 crown\n",
      "1 crowne\n",
      "1 crowning\n",
      "2 crt\n",
      "1 crudely\n",
      "5 cruise\n",
      "1 cruises\n",
      "6 crumbs\n",
      "2 crummy\n",
      "2 crunch\n",
      "1 crust\n",
      "1 crutches\n",
      "2 cry\n",
      "1 crystal\n",
      "5 cta\n",
      "1 cubes\n",
      "1 cubicle\n",
      "3 cubs\n",
      "1 cuddle\n",
      "1 cue\n",
      "6 cuisine\n",
      "1 cultural\n",
      "1 culturally\n",
      "4 culture\n",
      "9 cup\n",
      "1 cupcakes\n",
      "1 cups\n",
      "1 curb\n",
      "1 curbside\n",
      "1 curdling\n",
      "1 cures\n",
      "1 curled\n",
      "2 currency\n",
      "5 current\n",
      "6 currently\n",
      "3 curry\n",
      "1 cursing\n",
      "3 curt\n",
      "8 curtain\n",
      "13 curtains\n",
      "1 curtious\n",
      "1 curtis\n",
      "2 cushy\n",
      "1 cusine\n",
      "2 custom\n",
      "2 customary\n",
      "102 customer\n",
      "18 customers\n",
      "1 customize\n",
      "1 customizing\n",
      "10 cut\n",
      "4 cute\n",
      "1 cutesy\n",
      "2 cutter\n",
      "1 cutting\n",
      "1 cyber\n",
      "1 cycle\n",
      "1 dad\n",
      "11 daily\n",
      "1 dakota\n",
      "4 damage\n",
      "3 damaged\n",
      "1 damages\n",
      "1 damn\n",
      "3 damp\n",
      "2 dance\n",
      "1 dancer\n",
      "1 dancers\n",
      "2 dancing\n",
      "1 dander\n",
      "1 dandy\n",
      "4 dangerous\n",
      "1 daniel\n",
      "1 danish\n",
      "2 danishes\n",
      "1 dank\n",
      "1 dare\n",
      "23 dark\n",
      "1 darker\n",
      "1 database\n",
      "13 date\n",
      "19 dated\n",
      "6 dates\n",
      "32 daughter\n",
      "3 daughters\n",
      "1 dave\n",
      "6 david\n",
      "1 dawn\n",
      "285 day\n",
      "1 daycare\n",
      "1 daylight\n",
      "101 days\n",
      "2 daytime\n",
      "1 dble\n",
      "2 dc\n",
      "2 de\n",
      "1 deactivated\n",
      "9 dead\n",
      "2 deadline\n",
      "69 deal\n",
      "1 dealers\n",
      "4 dealing\n",
      "1 dealings\n",
      "6 deals\n",
      "6 dealt\n",
      "3 dear\n",
      "1 dearborn\n",
      "1 death\n",
      "4 debit\n",
      "4 dec\n",
      "2 decade\n",
      "1 decadence\n",
      "2 decades\n",
      "5 deceiving\n",
      "1 deceivingly\n",
      "7 december\n",
      "29 decent\n",
      "1 decently\n",
      "2 deceptively\n",
      "6 decide\n",
      "108 decided\n",
      "1 decidedly\n",
      "8 decision\n",
      "2 deck\n",
      "1 decked\n",
      "1 decker\n",
      "1 decks\n",
      "4 declined\n",
      "4 deco\n",
      "76 decor\n",
      "43 decorated\n",
      "4 decorating\n",
      "6 decoration\n",
      "3 decorations\n",
      "3 decorative\n",
      "1 decreased\n",
      "2 dedicated\n",
      "7 deep\n",
      "4 def\n",
      "1 default\n",
      "1 defeat\n",
      "1 defenitely\n",
      "18 definately\n",
      "9 definetly\n",
      "5 definite\n",
      "190 definitely\n",
      "2 definition\n",
      "2 definitly\n",
      "3 degree\n",
      "8 degrees\n",
      "2 delaware\n",
      "11 delayed\n",
      "3 delays\n",
      "35 delicious\n",
      "9 delight\n",
      "6 delighted\n",
      "5 delightful\n",
      "14 deliver\n",
      "30 delivered\n",
      "7 delivery\n",
      "20 deluxe\n",
      "2 demand\n",
      "4 demanded\n",
      "2 demonstrated\n",
      "3 denied\n",
      "3 dent\n",
      "2 dents\n",
      "3 depart\n",
      "2 departing\n",
      "6 department\n",
      "4 departure\n",
      "2 depending\n",
      "2 dept\n",
      "6 des\n",
      "2 descent\n",
      "6 describe\n",
      "6 described\n",
      "5 description\n",
      "2 descriptions\n",
      "2 deserved\n",
      "23 design\n",
      "13 designed\n",
      "7 designer\n",
      "2 designs\n",
      "2 desirable\n",
      "8 desired\n",
      "419 desk\n",
      "3 desks\n",
      "2 desperate\n",
      "45 despite\n",
      "5 dessert\n",
      "3 desserts\n",
      "2 dest\n",
      "8 destination\n",
      "2 destroyed\n",
      "12 detail\n",
      "8 details\n",
      "3 determined\n",
      "3 device\n",
      "4 dial\n",
      "6 diamond\n",
      "17 didnt\n",
      "12 die\n",
      "12 difference\n",
      "68 different\n",
      "25 difficult\n",
      "3 difficulty\n",
      "2 digital\n",
      "2 dim\n",
      "2 dime\n",
      "5 dimed\n",
      "3 dimly\n",
      "3 dine\n",
      "4 dined\n",
      "2 ding\n",
      "20 dingy\n",
      "56 dining\n",
      "80 dinner\n",
      "8 dinning\n",
      "2 dip\n",
      "6 direct\n",
      "5 directed\n",
      "4 direction\n",
      "17 directions\n",
      "17 directly\n",
      "3 directory\n",
      "9 dirt\n",
      "87 dirty\n",
      "2 disagreement\n",
      "6 disapointed\n",
      "4 disappoint\n",
      "111 disappointed\n",
      "20 disappointing\n",
      "21 disappointment\n",
      "4 disappointments\n",
      "6 disaster\n",
      "2 disconnected\n",
      "22 discount\n",
      "3 discounted\n",
      "10 discover\n",
      "19 discovered\n",
      "3 discuss\n",
      "4 disgusted\n",
      "14 disgusting\n",
      "3 dish\n",
      "5 dishes\n",
      "4 dishwasher\n",
      "2 disliked\n",
      "2 dismay\n",
      "4 display\n",
      "2 displayed\n",
      "2 displeased\n",
      "3 displeasure\n",
      "2 disposal\n",
      "5 disregarded\n",
      "3 disrepair\n",
      "2 dissapointed\n",
      "3 dissappointed\n",
      "2 dissatisfaction\n",
      "6 dissatisfied\n",
      "79 distance\n",
      "2 distasteful\n",
      "4 distinct\n",
      "2 distracted\n",
      "15 district\n",
      "11 disturb\n",
      "2 ditch\n",
      "3 division\n",
      "2 dna\n",
      "9 dock\n",
      "6 docking\n",
      "3 docks\n",
      "2 documents\n",
      "3 doesnt\n",
      "41 dog\n",
      "5 dogs\n",
      "5 doll\n",
      "9 dollar\n",
      "22 dollars\n",
      "60 done\n",
      "3 donna\n",
      "11 dont\n",
      "2 donuts\n",
      "161 door\n",
      "24 doorman\n",
      "17 doormen\n",
      "30 doors\n",
      "46 double\n",
      "4 doubles\n",
      "12 doubt\n",
      "2 doubts\n",
      "3 downgrade\n",
      "5 downhill\n",
      "3 downright\n",
      "5 downside\n",
      "34 downstairs\n",
      "165 downtown\n",
      "7 dozen\n",
      "3 drab\n",
      "2 dragged\n",
      "2 drain\n",
      "2 drained\n",
      "8 drake\n",
      "2 drank\n",
      "3 drapes\n",
      "2 draw\n",
      "2 drawback\n",
      "2 drawbacks\n",
      "2 drawer\n",
      "7 drawers\n",
      "4 dreadful\n",
      "6 dream\n",
      "3 dreary\n",
      "2 dress\n",
      "9 dressed\n",
      "5 dresser\n",
      "2 dressing\n",
      "2 drew\n",
      "7 dried\n",
      "2 drift\n",
      "29 drink\n",
      "6 drinking\n",
      "42 drinks\n",
      "5 drip\n",
      "4 dripped\n",
      "3 dripping\n",
      "16 drive\n",
      "5 driver\n",
      "2 drivers\n",
      "3 driving\n",
      "4 drop\n",
      "4 dropped\n",
      "3 dropping\n",
      "7 drove\n",
      "3 drunk\n",
      "2 drunks\n",
      "9 dry\n",
      "3 dryer\n",
      "2 dual\n",
      "40 due\n",
      "5 dump\n",
      "2 dumpster\n",
      "3 dumpsters\n",
      "2 dumpy\n",
      "6 duration\n",
      "14 dust\n",
      "6 dusty\n",
      "9 duty\n",
      "7 duvet\n",
      "4 dvd\n",
      "9 eager\n",
      "17 earlier\n",
      "49 early\n",
      "2 earn\n",
      "4 earned\n",
      "2 earplugs\n",
      "2 earrings\n",
      "11 ease\n",
      "2 easier\n",
      "21 easily\n",
      "64 east\n",
      "57 easy\n",
      "48 eat\n",
      "7 eaten\n",
      "18 eating\n",
      "2 echo\n",
      "3 eclectic\n",
      "4 edge\n",
      "4 edges\n",
      "2 effective\n",
      "2 effectively\n",
      "14 efficient\n",
      "7 effort\n",
      "2 efforts\n",
      "13 eggs\n",
      "2 eight\n",
      "54 either\n",
      "11 el\n",
      "2 elaborate\n",
      "3 elected\n",
      "10 elegance\n",
      "45 elegant\n",
      "4 elegantly\n",
      "3 elevated\n",
      "52 elevator\n",
      "42 elevators\n",
      "3 eleven\n",
      "3 elite\n",
      "72 else\n",
      "28 elsewhere\n",
      "16 email\n",
      "2 emailed\n",
      "3 emails\n",
      "2 embarrassing\n",
      "7 emergency\n",
      "2 employed\n",
      "22 employee\n",
      "38 employees\n",
      "2 employer\n",
      "12 empty\n",
      "4 encounter\n",
      "16 encountered\n",
      "63 end\n",
      "37 ended\n",
      "2 ends\n",
      "2 energized\n",
      "3 energy\n",
      "2 engine\n",
      "3 engineer\n",
      "4 english\n",
      "48 enjoy\n",
      "14 enjoyable\n",
      "100 enjoyed\n",
      "10 enjoying\n",
      "2 enjoyment\n",
      "5 eno\n",
      "5 enormous\n",
      "96 enough\n",
      "4 ensure\n",
      "10 enter\n",
      "21 entered\n",
      "13 entering\n",
      "6 entertainment\n",
      "49 entire\n",
      "3 entirely\n",
      "2 entitled\n",
      "23 entrance\n",
      "4 environment\n",
      "2 environmental\n",
      "2 equal\n",
      "3 equally\n",
      "2 equinox\n",
      "9 equipment\n",
      "16 equipped\n",
      "3 era\n",
      "2 erin\n",
      "12 error\n",
      "2 errors\n",
      "6 escape\n",
      "3 escorted\n",
      "77 especially\n",
      "4 essentially\n",
      "17 establishment\n",
      "2 establishments\n",
      "56 etc\n",
      "2 ethan\n",
      "2 eucalyptus\n",
      "5 europe\n",
      "9 european\n",
      "2 evan\n",
      "5 eve\n",
      "375 even\n",
      "41 evening\n",
      "2 evenings\n",
      "19 event\n",
      "5 events\n",
      "15 eventually\n",
      "169 ever\n",
      "138 every\n",
      "6 everybody\n",
      "61 everyone\n",
      "177 everything\n",
      "3 everytime\n",
      "18 everywhere\n",
      "2 evian\n",
      "5 evident\n",
      "2 evidently\n",
      "2 eww\n",
      "4 exact\n",
      "19 exactly\n",
      "5 example\n",
      "2 exceed\n",
      "7 exceeded\n",
      "2 exceeds\n",
      "2 excellence\n",
      "133 excellent\n",
      "17 except\n",
      "7 exception\n",
      "15 exceptional\n",
      "10 exceptionally\n",
      "2 excessively\n",
      "4 exchange\n",
      "28 excited\n",
      "4 excitement\n",
      "9 exciting\n",
      "3 exclusive\n",
      "4 excursion\n",
      "5 excuse\n",
      "14 executive\n",
      "4 exemplary\n",
      "7 exercise\n",
      "2 exhaust\n",
      "5 exhausted\n",
      "3 exhibit\n",
      "2 existant\n",
      "3 existent\n",
      "3 exit\n",
      "2 exited\n",
      "6 exorbitant\n",
      "2 exotic\n",
      "72 expect\n",
      "41 expectations\n",
      "80 expected\n",
      "38 expecting\n",
      "4 expedia\n",
      "6 expense\n",
      "3 expenses\n",
      "58 expensive\n",
      "280 experience\n",
      "23 experienced\n",
      "20 experiences\n",
      "4 experiencing\n",
      "2 experince\n",
      "6 explain\n",
      "13 explained\n",
      "2 explaining\n",
      "2 explicitly\n",
      "7 explore\n",
      "4 exploring\n",
      "4 exposed\n",
      "7 express\n",
      "3 expressed\n",
      "7 exquisite\n",
      "2 extend\n",
      "7 extended\n",
      "5 extensive\n",
      "4 exterior\n",
      "72 extra\n",
      "4 extras\n",
      "3 extravagant\n",
      "3 extreme\n",
      "100 extremely\n",
      "11 eye\n",
      "8 eyes\n",
      "3 fab\n",
      "2 faboulous\n",
      "2 fabric\n",
      "36 fabulous\n",
      "3 facade\n",
      "17 face\n",
      "15 facilities\n",
      "13 facility\n",
      "10 facing\n",
      "65 fact\n",
      "4 factor\n",
      "4 factory\n",
      "4 faded\n",
      "6 fail\n",
      "14 failed\n",
      "3 fails\n",
      "4 faint\n",
      "11 fair\n",
      "18 fairly\n",
      "72 fairmont\n",
      "3 fake\n",
      "9 fall\n",
      "5 fallen\n",
      "9 falling\n",
      "5 falls\n",
      "7 families\n",
      "103 family\n",
      "8 famous\n",
      "11 fan\n",
      "13 fancy\n",
      "2 fancypants\n",
      "74 fantastic\n",
      "71 far\n",
      "6 fare\n",
      "2 fashion\n",
      "4 fashioned\n",
      "22 fast\n",
      "4 faster\n",
      "2 father\n",
      "2 faucet\n",
      "15 fault\n",
      "7 favor\n",
      "37 favorite\n",
      "3 favourite\n",
      "4 fax\n",
      "4 fear\n",
      "6 feather\n",
      "3 feathers\n",
      "10 feature\n",
      "2 featured\n",
      "14 features\n",
      "2 featuring\n",
      "5 february\n",
      "24 fee\n",
      "124 feel\n",
      "30 feeling\n",
      "9 feels\n",
      "11 fees\n",
      "9 feet\n",
      "13 fell\n",
      "3 fellow\n",
      "110 felt\n",
      "4 festival\n",
      "2 fewer\n",
      "40 fi\n",
      "10 fiance\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4 fiancee\n",
      "10 field\n",
      "3 fifteen\n",
      "2 fifth\n",
      "2 fifty\n",
      "3 fight\n",
      "2 fighting\n",
      "12 figure\n",
      "12 figured\n",
      "2 fiji\n",
      "4 file\n",
      "5 filed\n",
      "3 fill\n",
      "15 filled\n",
      "3 filling\n",
      "2 film\n",
      "2 filter\n",
      "15 filthy\n",
      "7 final\n",
      "144 finally\n",
      "2 financial\n",
      "138 find\n",
      "9 finding\n",
      "56 fine\n",
      "8 finest\n",
      "5 finger\n",
      "2 fingertips\n",
      "3 finish\n",
      "11 finished\n",
      "2 finishing\n",
      "5 fire\n",
      "2 fireplaces\n",
      "3 fireworks\n",
      "5 firm\n",
      "284 first\n",
      "2 firstly\n",
      "8 fish\n",
      "11 fit\n",
      "67 fitness\n",
      "6 fitzpatrick\n",
      "28 five\n",
      "29 fix\n",
      "17 fixed\n",
      "15 fixtures\n",
      "2 flair\n",
      "50 flat\n",
      "7 flavor\n",
      "2 flavorless\n",
      "2 flaw\n",
      "2 flawless\n",
      "2 flew\n",
      "2 flexible\n",
      "23 flight\n",
      "5 flights\n",
      "2 floating\n",
      "2 flood\n",
      "2 flooded\n",
      "198 floor\n",
      "25 floors\n",
      "2 flow\n",
      "6 flowers\n",
      "4 fluffy\n",
      "3 flush\n",
      "3 flushed\n",
      "5 flushing\n",
      "3 fly\n",
      "6 flying\n",
      "2 foam\n",
      "3 focus\n",
      "3 focused\n",
      "2 folio\n",
      "8 folks\n",
      "6 follow\n",
      "4 followed\n",
      "14 following\n",
      "201 food\n",
      "3 foods\n",
      "3 fool\n",
      "3 fooled\n",
      "8 foot\n",
      "2 footsteps\n",
      "15 forced\n",
      "2 forcing\n",
      "2 ford\n",
      "3 foreign\n",
      "17 forever\n",
      "9 forget\n",
      "9 forgot\n",
      "6 forgotten\n",
      "7 form\n",
      "2 formal\n",
      "2 former\n",
      "2 forms\n",
      "7 forth\n",
      "2 forthcoming\n",
      "2 fortunate\n",
      "5 fortunately\n",
      "3 forty\n",
      "43 forward\n",
      "2 forwarded\n",
      "5 foul\n",
      "177 found\n",
      "3 fountain\n",
      "56 four\n",
      "2 fourth\n",
      "2 fowl\n",
      "3 francisco\n",
      "7 frankly\n",
      "2 frayed\n",
      "3 freak\n",
      "181 free\n",
      "4 freezing\n",
      "16 french\n",
      "13 frequent\n",
      "2 frequented\n",
      "9 frequently\n",
      "40 fresh\n",
      "2 freshener\n",
      "2 freshly\n",
      "11 friday\n",
      "18 fridge\n",
      "37 friend\n",
      "4 friendliest\n",
      "3 friendliness\n",
      "251 friendly\n",
      "57 friends\n",
      "2 fries\n",
      "318 front\n",
      "10 fruit\n",
      "5 frustrated\n",
      "8 frustrating\n",
      "3 frustration\n",
      "6 ft\n",
      "2 fulfill\n",
      "72 full\n",
      "14 fully\n",
      "47 fun\n",
      "5 function\n",
      "3 functional\n",
      "8 funky\n",
      "3 funny\n",
      "4 furious\n",
      "26 furnished\n",
      "18 furnishings\n",
      "54 furniture\n",
      "2 furnitures\n",
      "2 furry\n",
      "3 furthermore\n",
      "2 fuss\n",
      "2 fussing\n",
      "3 fussy\n",
      "3 futon\n",
      "33 future\n",
      "2 fyi\n",
      "2 gain\n",
      "8 game\n",
      "3 gap\n",
      "16 garage\n",
      "9 garbage\n",
      "3 garden\n",
      "3 garish\n",
      "5 gas\n",
      "96 gave\n",
      "3 gem\n",
      "26 general\n",
      "9 generally\n",
      "4 generic\n",
      "4 generous\n",
      "2 geneva\n",
      "3 gentle\n",
      "5 gentleman\n",
      "2 gentlemen\n",
      "2 genuine\n",
      "5 genuinely\n",
      "2 gesture\n",
      "442 get\n",
      "31 getaway\n",
      "7 gets\n",
      "61 getting\n",
      "3 giant\n",
      "20 gift\n",
      "2 giggling\n",
      "2 gino\n",
      "24 girl\n",
      "2 girlfriend\n",
      "7 girlfriends\n",
      "16 girls\n",
      "82 give\n",
      "83 given\n",
      "8 gives\n",
      "8 giving\n",
      "19 glad\n",
      "5 gladly\n",
      "3 glamorous\n",
      "2 glamourous\n",
      "9 glance\n",
      "22 glass\n",
      "10 glasses\n",
      "2 glitch\n",
      "2 glossy\n",
      "3 glowing\n",
      "2 gluten\n",
      "3 gm\n",
      "243 go\n",
      "7 god\n",
      "2 godsend\n",
      "11 goes\n",
      "135 going\n",
      "13 gold\n",
      "2 golden\n",
      "7 goldfish\n",
      "15 gone\n",
      "327 good\n",
      "3 goodies\n",
      "4 goodness\n",
      "2 gooey\n",
      "32 gorgeous\n",
      "329 got\n",
      "7 gotten\n",
      "3 gouge\n",
      "2 gouging\n",
      "7 gourmet\n",
      "5 grab\n",
      "2 grabbed\n",
      "3 grace\n",
      "6 gracious\n",
      "3 grade\n",
      "2 grain\n",
      "16 grand\n",
      "2 grander\n",
      "2 grandeur\n",
      "2 grandma\n",
      "2 granite\n",
      "17 grant\n",
      "11 granted\n",
      "2 gratis\n",
      "4 gratuity\n",
      "2 gray\n",
      "2 grease\n",
      "3 greasy\n",
      "706 great\n",
      "2 greater\n",
      "5 greatest\n",
      "3 greatly\n",
      "5 green\n",
      "4 greet\n",
      "50 greeted\n",
      "4 greeting\n",
      "2 grey\n",
      "4 grill\n",
      "3 grilled\n",
      "2 gripe\n",
      "2 groaned\n",
      "2 groceries\n",
      "9 grocery\n",
      "3 grooming\n",
      "13 gross\n",
      "8 ground\n",
      "20 group\n",
      "3 groups\n",
      "3 grout\n",
      "3 grudgingly\n",
      "5 guarantee\n",
      "5 guaranteed\n",
      "27 guess\n",
      "2 guessed\n",
      "90 guest\n",
      "6 guestroom\n",
      "3 guestrooms\n",
      "105 guests\n",
      "4 guide\n",
      "2 guiding\n",
      "2 guitar\n",
      "4 gum\n",
      "21 guy\n",
      "6 guys\n",
      "44 gym\n",
      "3 hail\n",
      "31 hair\n",
      "5 hairdryer\n",
      "7 hairs\n",
      "52 half\n",
      "23 hall\n",
      "4 halls\n",
      "28 hallway\n",
      "21 hallways\n",
      "4 hampton\n",
      "12 hancock\n",
      "26 hand\n",
      "7 handed\n",
      "2 handful\n",
      "5 handicapped\n",
      "13 handle\n",
      "3 handled\n",
      "2 handling\n",
      "6 hands\n",
      "2 handsome\n",
      "9 handy\n",
      "9 hang\n",
      "3 hangers\n",
      "6 hanging\n",
      "11 happen\n",
      "19 happened\n",
      "3 happening\n",
      "4 happens\n",
      "3 happier\n",
      "6 happily\n",
      "44 happy\n",
      "134 hard\n",
      "10 hardly\n",
      "7 hare\n",
      "2 harry\n",
      "10 hassle\n",
      "7 hate\n",
      "2 hated\n",
      "2 hbo\n",
      "6 hd\n",
      "17 head\n",
      "3 headache\n",
      "3 headboard\n",
      "2 headboards\n",
      "9 headed\n",
      "3 heading\n",
      "2 headquarters\n",
      "9 health\n",
      "62 hear\n",
      "47 heard\n",
      "4 hearing\n",
      "36 heart\n",
      "4 heartbeat\n",
      "2 heartily\n",
      "8 heat\n",
      "3 heated\n",
      "4 heater\n",
      "6 heating\n",
      "4 heaven\n",
      "7 heavy\n",
      "4 hefty\n",
      "3 height\n",
      "14 held\n",
      "5 hell\n",
      "6 hello\n",
      "68 help\n",
      "30 helped\n",
      "182 helpful\n",
      "4 helpfull\n",
      "10 helping\n",
      "11 hesitate\n",
      "7 hesitation\n",
      "7 hi\n",
      "3 hidden\n",
      "3 hide\n",
      "3 hideous\n",
      "111 high\n",
      "23 higher\n",
      "5 highest\n",
      "6 highlight\n",
      "95 highly\n",
      "2 highway\n",
      "2 hike\n",
      "155 hilton\n",
      "11 hip\n",
      "19 historic\n",
      "4 historical\n",
      "6 history\n",
      "16 hit\n",
      "2 ho\n",
      "22 hold\n",
      "3 holder\n",
      "3 holding\n",
      "7 hole\n",
      "24 holiday\n",
      "115 home\n",
      "3 homeless\n",
      "46 homewood\n",
      "5 homey\n",
      "2 honest\n",
      "10 honestly\n",
      "12 honeymoon\n",
      "9 honor\n",
      "3 honors\n",
      "3 hook\n",
      "4 hop\n",
      "18 hope\n",
      "7 hoped\n",
      "7 hopefully\n",
      "9 hopes\n",
      "14 hoping\n",
      "2 hopkins\n",
      "2 hops\n",
      "2 horrendous\n",
      "34 horrible\n",
      "6 horribly\n",
      "2 horrid\n",
      "3 horrific\n",
      "2 horror\n",
      "3 hors\n",
      "3 hospitable\n",
      "7 hospital\n",
      "13 hospitality\n",
      "4 host\n",
      "5 hosting\n",
      "57 hot\n",
      "2654 hotel\n",
      "242 hotels\n",
      "15 hotwire\n",
      "116 hour\n",
      "86 hours\n",
      "81 house\n",
      "2 housecleaning\n",
      "4 housekeeper\n",
      "67 housekeeping\n",
      "106 however\n",
      "2 hr\n",
      "7 hrh\n",
      "8 hrs\n",
      "73 huge\n",
      "3 human\n",
      "2 humid\n",
      "2 humming\n",
      "5 hundred\n",
      "3 hundreds\n",
      "8 hung\n",
      "7 hungry\n",
      "2 hunk\n",
      "2 hurry\n",
      "150 husband\n",
      "2 husbands\n",
      "3 hustle\n",
      "4 hvac\n",
      "77 hyatt\n",
      "3 hype\n",
      "4 hyped\n",
      "3 hypo\n",
      "3 hypoallergenic\n",
      "22 ice\n",
      "2 icebucket\n",
      "3 icing\n",
      "2 id\n",
      "22 idea\n",
      "13 ideal\n",
      "2 ideally\n",
      "2 idiot\n",
      "2 idiots\n",
      "4 ie\n",
      "8 ignore\n",
      "10 ignored\n",
      "3 ihome\n",
      "8 ikea\n",
      "7 il\n",
      "8 ill\n",
      "7 illinois\n",
      "2 illusion\n",
      "4 im\n",
      "3 images\n",
      "20 imagine\n",
      "6 imagined\n",
      "13 immaculate\n",
      "3 immaculately\n",
      "2 immediate\n",
      "42 immediately\n",
      "2 imo\n",
      "2 impecable\n",
      "6 impeccable\n",
      "6 impeccably\n",
      "2 impersonal\n",
      "4 impolite\n",
      "14 important\n",
      "6 importantly\n",
      "11 impossible\n",
      "55 impressed\n",
      "13 impression\n",
      "4 impressions\n",
      "13 impressive\n",
      "2 improve\n",
      "2 improvement\n",
      "2 inability\n",
      "4 inadequate\n",
      "2 inappropriate\n",
      "3 inattentive\n",
      "12 inch\n",
      "3 inches\n",
      "10 incident\n",
      "3 incidentals\n",
      "7 include\n",
      "36 included\n",
      "7 includes\n",
      "38 including\n",
      "4 incompetence\n",
      "5 incompetent\n",
      "12 inconvenience\n",
      "5 inconveniences\n",
      "2 inconveniencing\n",
      "2 inconvenient\n",
      "5 incorrect\n",
      "26 incredible\n",
      "29 incredibly\n",
      "2 incur\n",
      "11 indeed\n",
      "7 indicated\n",
      "7 indifferent\n",
      "4 individual\n",
      "3 individuals\n",
      "24 indoor\n",
      "2 indoors\n",
      "2 indulge\n",
      "9 industry\n",
      "3 inept\n",
      "3 inexcusable\n",
      "2 inexpensive\n",
      "2 inexperienced\n",
      "2 inexplicably\n",
      "2 inflated\n",
      "2 info\n",
      "2 inform\n",
      "16 information\n",
      "2 informative\n",
      "28 informed\n",
      "4 initial\n",
      "7 initially\n",
      "2 injury\n",
      "31 inn\n",
      "2 innovative\n",
      "6 inquire\n",
      "2 inquired\n",
      "4 insects\n",
      "35 inside\n",
      "2 insincere\n",
      "11 insisted\n",
      "3 insisting\n",
      "3 inspect\n",
      "5 inspection\n",
      "2 inspiring\n",
      "5 instantly\n",
      "54 instead\n",
      "11 institute\n",
      "2 instructed\n",
      "3 instructions\n",
      "3 insulation\n",
      "5 insult\n",
      "2 insulting\n",
      "2 insurance\n",
      "3 intend\n",
      "4 intended\n",
      "2 intense\n",
      "2 intention\n",
      "57 intercontinental\n",
      "2 interest\n",
      "7 interested\n",
      "11 interesting\n",
      "2 interestingly\n",
      "2 interests\n",
      "8 interior\n",
      "2 international\n",
      "124 internet\n",
      "2 interrupted\n",
      "2 intimate\n",
      "2 introduction\n",
      "2 intrusive\n",
      "2 investigate\n",
      "2 invisible\n",
      "14 inviting\n",
      "5 involved\n",
      "2 iphone\n",
      "21 ipod\n",
      "8 irish\n",
      "10 iron\n",
      "3 ironing\n",
      "4 isnt\n",
      "31 issue\n",
      "23 issues\n",
      "4 italian\n",
      "2 itchy\n",
      "6 item\n",
      "32 items\n",
      "4 ive\n",
      "3 jack\n",
      "8 jacuzzi\n",
      "90 james\n",
      "2 jamie\n",
      "4 january\n",
      "2 jaunt\n",
      "2 jaw\n",
      "3 jazz\n",
      "3 jeans\n",
      "7 jet\n",
      "3 jewel\n",
      "30 job\n",
      "2 jobs\n",
      "3 joe\n",
      "1 joes\n",
      "2 jogging\n",
      "10 john\n",
      "3 join\n",
      "2 joining\n",
      "6 joke\n",
      "9 juice\n",
      "16 july\n",
      "3 jump\n",
      "8 june\n",
      "2 jungle\n",
      "10 junior\n",
      "2 justice\n",
      "2 justify\n",
      "3 keefer\n",
      "33 keep\n",
      "7 keeping\n",
      "4 keeps\n",
      "45 kept\n",
      "37 key\n",
      "2 keycard\n",
      "14 keys\n",
      "4 kick\n",
      "2 kicker\n",
      "11 kid\n",
      "3 kidding\n",
      "47 kids\n",
      "3 kiehls\n",
      "30 kimpton\n",
      "4 kimptons\n",
      "47 kind\n",
      "3 kinda\n",
      "5 kinds\n",
      "102 king\n",
      "4 kings\n",
      "3 kinzie\n",
      "2 kiss\n",
      "6 kit\n",
      "33 kitchen\n",
      "2 kitchenette\n",
      "6 kitty\n",
      "2 kleenex\n",
      "42 knew\n",
      "58 knickerbocker\n",
      "5 knock\n",
      "4 knocked\n",
      "3 knocking\n",
      "102 know\n",
      "5 knowing\n",
      "2 knowledgable\n",
      "3 knowledge\n",
      "9 knowledgeable\n",
      "10 known\n",
      "5 knows\n",
      "2 ky\n",
      "5 la\n",
      "4 labor\n",
      "31 lack\n",
      "7 lacked\n",
      "15 lacking\n",
      "4 lackluster\n",
      "4 lacks\n",
      "4 ladies\n",
      "29 lady\n",
      "2 lag\n",
      "7 laid\n",
      "51 lake\n",
      "3 lakeshore\n",
      "2 lame\n",
      "6 lamp\n",
      "7 lamps\n",
      "3 language\n",
      "4 lap\n",
      "2 laps\n",
      "11 laptop\n",
      "118 large\n",
      "3 largely\n",
      "16 larger\n",
      "4 largest\n",
      "132 last\n",
      "2 lasted\n",
      "5 lastly\n",
      "67 late\n",
      "71 later\n",
      "3 latest\n",
      "2 latte\n",
      "2 laundered\n",
      "8 laundry\n",
      "3 lavish\n",
      "4 laws\n",
      "3 lay\n",
      "9 layout\n",
      "2 lb\n",
      "8 lcd\n",
      "5 le\n",
      "2 lead\n",
      "3 leading\n",
      "2 leak\n",
      "5 leaked\n",
      "2 leaning\n",
      "5 learn\n",
      "6 learned\n",
      "62 least\n",
      "59 leave\n",
      "5 leaves\n",
      "28 leaving\n",
      "2 lebron\n",
      "2 led\n",
      "2 ledge\n",
      "113 left\n",
      "7 leg\n",
      "2 legged\n",
      "2 legs\n",
      "9 leisure\n",
      "2 lend\n",
      "5 length\n",
      "3 lengthy\n",
      "65 less\n",
      "3 lesson\n",
      "66 let\n",
      "7 lets\n",
      "10 letter\n",
      "5 letting\n",
      "3 lettuce\n",
      "34 level\n",
      "4 levels\n",
      "2 lid\n",
      "4 lie\n",
      "30 life\n",
      "4 lifetime\n",
      "6 lift\n",
      "30 light\n",
      "3 lightbulb\n",
      "2 lighted\n",
      "9 lighting\n",
      "13 lights\n",
      "436 like\n",
      "34 liked\n",
      "7 likely\n",
      "4 liking\n",
      "12 limited\n",
      "2 limp\n",
      "2 lincoln\n",
      "79 line\n",
      "4 lined\n",
      "5 linen\n",
      "33 linens\n",
      "6 lines\n",
      "2 lingering\n",
      "2 link\n",
      "2 linnens\n",
      "4 liquor\n",
      "18 list\n",
      "3 listed\n",
      "5 listen\n",
      "5 listening\n",
      "14 lit\n",
      "2 lite\n",
      "13 literally\n",
      "2 littered\n",
      "121 little\n",
      "29 live\n",
      "3 lived\n",
      "3 lives\n",
      "19 living\n",
      "2 loaded\n",
      "3 loading\n",
      "235 lobby\n",
      "23 local\n",
      "3 locate\n",
      "96 located\n",
      "2 locating\n",
      "393 location\n",
      "10 locations\n",
      "2 lock\n",
      "8 locked\n",
      "3 locker\n",
      "9 lockwood\n",
      "2 lodge\n",
      "4 lodging\n",
      "2 log\n",
      "3 logo\n",
      "3 london\n",
      "124 long\n",
      "29 longer\n",
      "92 look\n",
      "114 looked\n",
      "147 looking\n",
      "37 looks\n",
      "27 loop\n",
      "2 los\n",
      "4 lose\n",
      "2 losing\n",
      "29 lost\n",
      "68 lot\n",
      "4 lotion\n",
      "36 lots\n",
      "38 loud\n",
      "2 loudly\n",
      "2 louisville\n",
      "24 lounge\n",
      "3 lounges\n",
      "57 love\n",
      "106 loved\n",
      "45 lovely\n",
      "5 loves\n",
      "21 low\n",
      "13 lower\n",
      "5 loyalty\n",
      "6 luck\n",
      "2 lucked\n",
      "8 luckily\n",
      "10 lucky\n",
      "4 lug\n",
      "37 luggage\n",
      "7 lukewarm\n",
      "4 lumpy\n",
      "14 lunch\n",
      "2 lure\n",
      "2 lured\n",
      "2 luster\n",
      "2 luxuary\n",
      "2 luxuries\n",
      "65 luxurious\n",
      "2 luxuriously\n",
      "102 luxury\n",
      "8 lying\n",
      "10 machine\n",
      "11 machines\n",
      "2 macys\n",
      "4 mad\n",
      "262 made\n",
      "8 mag\n",
      "2 magnificant\n",
      "64 magnificent\n",
      "6 magnificient\n",
      "35 maid\n",
      "10 maids\n",
      "5 mail\n",
      "2 mailed\n",
      "27 main\n",
      "4 mainly\n",
      "3 maintain\n",
      "15 maintained\n",
      "2 maintaining\n",
      "17 maintenance\n",
      "2 majestic\n",
      "22 major\n",
      "158 make\n",
      "3 makeover\n",
      "15 maker\n",
      "33 makes\n",
      "2 makeup\n",
      "53 making\n",
      "2 malfunctioning\n",
      "6 mall\n",
      "23 man\n",
      "4 manage\n",
      "9 managed\n",
      "31 management\n",
      "87 manager\n",
      "12 managers\n",
      "2 managing\n",
      "4 manhattan\n",
      "4 manner\n",
      "2 mansion\n",
      "2 mansions\n",
      "147 many\n",
      "3 map\n",
      "4 maps\n",
      "3 marathon\n",
      "14 marble\n",
      "7 march\n",
      "2 marginally\n",
      "3 marijuana\n",
      "9 mark\n",
      "2 marked\n",
      "3 market\n",
      "4 marketing\n",
      "2 marks\n",
      "2 marley\n",
      "8 married\n",
      "12 marriott\n",
      "8 martini\n",
      "4 martinis\n",
      "4 mass\n",
      "21 massage\n",
      "4 massages\n",
      "2 masseurs\n",
      "3 masseuse\n",
      "5 massive\n",
      "2 mat\n",
      "8 match\n",
      "5 matched\n",
      "3 matches\n",
      "4 materials\n",
      "17 matter\n",
      "2 mattered\n",
      "7 matters\n",
      "21 mattress\n",
      "8 mattresses\n",
      "2 max\n",
      "44 may\n",
      "28 maybe\n",
      "2 mccormick\n",
      "2 mcdonald\n",
      "33 meal\n",
      "9 meals\n",
      "15 mean\n",
      "5 meaning\n",
      "14 means\n",
      "7 meant\n",
      "3 meantime\n",
      "2 measures\n",
      "3 meat\n",
      "2 meats\n",
      "2 mechanical\n",
      "21 mediocre\n",
      "3 medium\n",
      "12 meet\n",
      "51 meeting\n",
      "12 meetings\n",
      "2 melted\n",
      "28 member\n",
      "19 members\n",
      "9 membership\n",
      "4 memorabilia\n",
      "7 memorable\n",
      "5 memorial\n",
      "4 memories\n",
      "5 memory\n",
      "11 men\n",
      "2 mental\n",
      "33 mention\n",
      "19 mentioned\n",
      "2 mentioning\n",
      "35 menu\n",
      "3 menus\n",
      "3 mere\n",
      "4 merely\n",
      "2 meridian\n",
      "6 mess\n",
      "2 message\n",
      "6 messed\n",
      "3 messy\n",
      "28 met\n",
      "3 metal\n",
      "2 metro\n",
      "2 metropolitan\n",
      "3 mi\n",
      "3 michelle\n",
      "138 michigan\n",
      "5 microwave\n",
      "10 mid\n",
      "16 middle\n",
      "7 midnight\n",
      "8 midway\n",
      "2 midwest\n",
      "2 miffed\n",
      "47 might\n",
      "2 mignon\n",
      "5 mildew\n",
      "84 mile\n",
      "4 miles\n",
      "8 milk\n",
      "23 millenium\n",
      "65 millennium\n",
      "5 million\n",
      "7 min\n",
      "22 mind\n",
      "2 minded\n",
      "2 minds\n",
      "16 mine\n",
      "32 mini\n",
      "18 minibar\n",
      "4 minimal\n",
      "2 minimalist\n",
      "3 minimum\n",
      "15 minor\n",
      "16 mins\n",
      "4 minus\n",
      "46 minute\n",
      "160 minutes\n",
      "7 miracle\n",
      "12 mirror\n",
      "2 mirrors\n",
      "6 miserable\n",
      "2 misfortune\n",
      "9 miss\n",
      "12 missed\n",
      "12 missing\n",
      "28 mistake\n",
      "3 mistaken\n",
      "2 mistakes\n",
      "7 mixed\n",
      "2 moderate\n",
      "3 moderately\n",
      "103 modern\n",
      "2 moist\n",
      "12 mold\n",
      "4 moldy\n",
      "5 mom\n",
      "29 moment\n",
      "5 moments\n",
      "70 monaco\n",
      "7 monday\n",
      "102 money\n",
      "3 monoco\n",
      "19 month\n",
      "17 months\n",
      "8 mood\n",
      "152 morning\n",
      "3 mornings\n",
      "9 mostly\n",
      "25 motel\n",
      "6 motels\n",
      "8 mother\n",
      "9 mouth\n",
      "2 mouths\n",
      "2 mouthwash\n",
      "30 move\n",
      "32 moved\n",
      "7 movie\n",
      "4 movies\n",
      "4 moving\n",
      "2 mp\n",
      "2 mph\n",
      "4 mr\n",
      "2 mrs\n",
      "206 much\n",
      "3 muffin\n",
      "9 muffins\n",
      "2 muffled\n",
      "2 muggy\n",
      "2 multilingual\n",
      "12 multiple\n",
      "20 museum\n",
      "17 museums\n",
      "29 music\n",
      "3 musical\n",
      "4 musicians\n",
      "3 musky\n",
      "62 must\n",
      "12 musty\n",
      "2 muted\n",
      "3 mysterious\n",
      "45 name\n",
      "6 named\n",
      "7 names\n",
      "4 nap\n",
      "2 naperville\n",
      "3 narrow\n",
      "4 nasty\n",
      "5 natural\n",
      "4 naturally\n",
      "3 navigate\n",
      "46 navy\n",
      "2 nbc\n",
      "15 nd\n",
      "62 near\n",
      "34 nearby\n",
      "2 nearest\n",
      "26 nearly\n",
      "12 neat\n",
      "2 necessarily\n",
      "108 need\n",
      "69 needed\n",
      "5 needing\n",
      "22 needless\n",
      "29 needs\n",
      "28 negative\n",
      "3 negatives\n",
      "3 neglected\n",
      "2 neighbor\n",
      "18 neighborhood\n",
      "2 neighborhoods\n",
      "5 neighboring\n",
      "12 neighbors\n",
      "2 neighbours\n",
      "12 neither\n",
      "2 nerve\n",
      "3 nervous\n",
      "3 network\n",
      "249 never\n",
      "107 new\n",
      "3 newer\n",
      "5 newly\n",
      "7 news\n",
      "9 newspaper\n",
      "257 next\n",
      "393 nice\n",
      "18 nicely\n",
      "19 nicer\n",
      "7 nicest\n",
      "4 nickel\n",
      "2 nickle\n",
      "476 night\n",
      "2 nightclub\n",
      "7 nightlife\n",
      "4 nightly\n",
      "8 nightmare\n",
      "152 nights\n",
      "2 nightstands\n",
      "2 nina\n",
      "4 nite\n",
      "2 nix\n",
      "19 nobody\n",
      "94 noise\n",
      "7 noises\n",
      "26 noisy\n",
      "2 nominal\n",
      "64 non\n",
      "19 none\n",
      "4 nonsmoking\n",
      "2 nook\n",
      "5 noon\n",
      "3 nordstrom\n",
      "3 nordstroms\n",
      "16 normal\n",
      "15 normally\n",
      "31 north\n",
      "2 notably\n",
      "21 notch\n",
      "20 note\n",
      "6 noted\n",
      "120 nothing\n",
      "12 notice\n",
      "35 noticed\n",
      "3 notified\n",
      "2 noting\n",
      "4 november\n",
      "9 nowhere\n",
      "3 nt\n",
      "24 number\n",
      "11 numerous\n",
      "2 nw\n",
      "2 ny\n",
      "3 nyc\n",
      "2 obese\n",
      "2 obtain\n",
      "4 obvious\n",
      "28 obviously\n",
      "6 occasion\n",
      "2 occasionally\n",
      "4 occasions\n",
      "2 occupant\n",
      "2 occupants\n",
      "4 occupied\n",
      "2 ocean\n",
      "5 october\n",
      "5 odd\n",
      "3 oddly\n",
      "22 odor\n",
      "78 offer\n",
      "69 offered\n",
      "6 offering\n",
      "17 offers\n",
      "19 office\n",
      "20 often\n",
      "26 oh\n",
      "2 ohare\n",
      "2 oil\n",
      "2 oj\n",
      "45 ok\n",
      "11 okay\n",
      "117 old\n",
      "17 older\n",
      "3 olds\n",
      "2 omelet\n",
      "2 omelettes\n",
      "79 omni\n",
      "571 one\n",
      "12 ones\n",
      "41 online\n",
      "11 onto\n",
      "63 open\n",
      "21 opened\n",
      "6 opening\n",
      "2 operated\n",
      "2 operating\n",
      "3 operator\n",
      "12 opinion\n",
      "5 opportunity\n",
      "4 opposed\n",
      "9 opposite\n",
      "7 opted\n",
      "20 option\n",
      "37 options\n",
      "5 orange\n",
      "2 orbitz\n",
      "45 order\n",
      "57 ordered\n",
      "3 ordering\n",
      "3 orders\n",
      "8 ordinary\n",
      "2 organized\n",
      "2 orginal\n",
      "5 original\n",
      "18 originally\n",
      "2 orlando\n",
      "2 osco\n",
      "38 others\n",
      "11 otherwise\n",
      "2 ottoman\n",
      "2 ouch\n",
      "11 outdated\n",
      "2 outdoor\n",
      "4 outing\n",
      "2 outlet\n",
      "4 outlets\n",
      "2 outline\n",
      "9 outrageous\n",
      "3 outrageously\n",
      "65 outside\n",
      "14 outstanding\n",
      "128 overall\n",
      "3 overbooked\n",
      "2 overcharge\n",
      "2 overcharged\n",
      "2 overcooked\n",
      "2 overflowed\n",
      "2 overheard\n",
      "3 overlook\n",
      "8 overlooked\n",
      "10 overlooking\n",
      "2 overly\n",
      "7 overnight\n",
      "33 overpriced\n",
      "3 overrated\n",
      "2 oversized\n",
      "4 overwhelmed\n",
      "2 overwhelming\n",
      "3 overwhelmingly\n",
      "2 owned\n",
      "5 owners\n",
      "7 pack\n",
      "38 package\n",
      "4 packages\n",
      "10 packed\n",
      "3 packing\n",
      "3 pad\n",
      "2 pages\n",
      "94 paid\n",
      "2 pain\n",
      "2 painful\n",
      "4 painless\n",
      "12 paint\n",
      "5 painted\n",
      "2 paintings\n",
      "5 pair\n",
      "6 palm\n",
      "50 palmer\n",
      "2 palms\n",
      "3 pamper\n",
      "10 pampered\n",
      "2 pampering\n",
      "3 panel\n",
      "2 pantry\n",
      "40 paper\n",
      "3 papers\n",
      "17 par\n",
      "2 parade\n",
      "3 paradise\n",
      "2 pardon\n",
      "8 parents\n",
      "3 paris\n",
      "99 park\n",
      "5 parked\n",
      "104 parking\n",
      "4 parks\n",
      "75 part\n",
      "4 partial\n",
      "11 particular\n",
      "23 particularly\n",
      "3 parties\n",
      "2 partner\n",
      "5 parts\n",
      "29 party\n",
      "14 pass\n",
      "10 passed\n",
      "2 passengers\n",
      "8 passes\n",
      "4 passing\n",
      "40 past\n",
      "2 pasta\n",
      "6 pastries\n",
      "3 pastry\n",
      "2 patches\n",
      "3 path\n",
      "3 pathetic\n",
      "4 patience\n",
      "2 patiently\n",
      "2 patron\n",
      "5 patrons\n",
      "2 patterns\n",
      "2 paul\n",
      "81 pay\n",
      "5 payed\n",
      "41 paying\n",
      "2 payment\n",
      "3 peace\n",
      "7 peaceful\n",
      "2 pedicure\n",
      "12 peeling\n",
      "2 peeve\n",
      "3 pending\n",
      "9 peninsula\n",
      "2 penninsula\n",
      "3 penny\n",
      "3 penthouse\n",
      "148 people\n",
      "48 per\n",
      "2 percentage\n",
      "100 perfect\n",
      "3 perfection\n",
      "14 perfectly\n",
      "16 perhaps\n",
      "8 period\n",
      "4 perk\n",
      "5 perks\n",
      "3 permeated\n",
      "2 permitted\n",
      "87 person\n",
      "2 personable\n",
      "40 personal\n",
      "4 personality\n",
      "2 personalized\n",
      "8 personally\n",
      "7 personnel\n",
      "2 pest\n",
      "44 pet\n",
      "24 pets\n",
      "6 phenomenal\n",
      "103 phone\n",
      "2 phoned\n",
      "5 phones\n",
      "2 photo\n",
      "2 photographs\n",
      "13 photos\n",
      "4 physical\n",
      "5 physically\n",
      "16 pick\n",
      "19 picked\n",
      "2 picking\n",
      "2 picks\n",
      "7 picky\n",
      "2 pics\n",
      "13 picture\n",
      "3 pictured\n",
      "28 pictures\n",
      "2 pie\n",
      "3 piece\n",
      "2 pieces\n",
      "43 pier\n",
      "25 pillow\n",
      "2 pillowcases\n",
      "61 pillows\n",
      "2 pinch\n",
      "5 pipes\n",
      "9 pizza\n",
      "2 pizzas\n",
      "2 pl\n",
      "286 place\n",
      "20 placed\n",
      "65 places\n",
      "3 placing\n",
      "2 plague\n",
      "9 plain\n",
      "27 plan\n",
      "3 plane\n",
      "2 planetarium\n",
      "15 planned\n",
      "14 planning\n",
      "6 plans\n",
      "16 plasma\n",
      "2 plasmas\n",
      "4 plastic\n",
      "7 plate\n",
      "2 platform\n",
      "8 play\n",
      "4 player\n",
      "6 playing\n",
      "59 pleasant\n",
      "13 pleasantly\n",
      "21 please\n",
      "37 pleased\n",
      "2 pleasent\n",
      "4 pleasing\n",
      "3 pleasurable\n",
      "24 pleasure\n",
      "2 plentiful\n",
      "30 plenty\n",
      "3 plug\n",
      "6 plumbing\n",
      "41 plus\n",
      "13 plush\n",
      "65 pm\n",
      "2 pocket\n",
      "42 point\n",
      "6 pointed\n",
      "11 points\n",
      "2 poking\n",
      "4 police\n",
      "14 policy\n",
      "28 polite\n",
      "3 politely\n",
      "117 pool\n",
      "2 pools\n",
      "42 poor\n",
      "15 poorly\n",
      "2 pops\n",
      "6 popular\n",
      "4 portion\n",
      "4 portions\n",
      "2 portray\n",
      "2 portrayed\n",
      "4 position\n",
      "23 positive\n",
      "2 positives\n",
      "18 possible\n",
      "9 possibly\n",
      "3 post\n",
      "6 posted\n",
      "2 poster\n",
      "2 posters\n",
      "2 posting\n",
      "4 pot\n",
      "2 powder\n",
      "2 power\n",
      "2 powerful\n",
      "6 practically\n",
      "2 praise\n",
      "11 pre\n",
      "2 precise\n",
      "15 prefer\n",
      "3 preferences\n",
      "9 preferred\n",
      "2 pregnant\n",
      "3 premier\n",
      "2 premiere\n",
      "4 premises\n",
      "18 premium\n",
      "3 prepaid\n",
      "5 prepare\n",
      "16 prepared\n",
      "3 presence\n",
      "5 present\n",
      "2 presentation\n",
      "2 president\n",
      "4 presidential\n",
      "2 pressed\n",
      "19 pressure\n",
      "2 presumably\n",
      "2 pretended\n",
      "4 pretentious\n",
      "53 pretty\n",
      "25 previous\n",
      "10 previously\n",
      "184 price\n",
      "21 priced\n",
      "42 priceline\n",
      "37 prices\n",
      "13 pricey\n",
      "2 pricing\n",
      "3 primarily\n",
      "9 prime\n",
      "6 primehouse\n",
      "6 print\n",
      "4 printed\n",
      "4 printing\n",
      "27 prior\n",
      "5 priority\n",
      "3 prison\n",
      "4 pristine\n",
      "7 privacy\n",
      "5 private\n",
      "2 priviledges\n",
      "2 prob\n",
      "33 probably\n",
      "74 problem\n",
      "62 problems\n",
      "2 procedure\n",
      "4 proceeded\n",
      "20 process\n",
      "2 processed\n",
      "3 produced\n",
      "2 product\n",
      "15 products\n",
      "29 professional\n",
      "2 professionalism\n",
      "2 professionally\n",
      "2 professionals\n",
      "2 profile\n",
      "14 program\n",
      "2 programs\n",
      "2 prohibitive\n",
      "2 prolonged\n",
      "8 promise\n",
      "19 promised\n",
      "5 promises\n",
      "2 promising\n",
      "10 prompt\n",
      "7 promptly\n",
      "3 proper\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "14 properly\n",
      "15 properties\n",
      "46 property\n",
      "11 pros\n",
      "2 prove\n",
      "4 proved\n",
      "21 provide\n",
      "41 provided\n",
      "9 provides\n",
      "3 providing\n",
      "9 proximity\n",
      "2 ps\n",
      "4 pub\n",
      "22 public\n",
      "12 pull\n",
      "7 pulled\n",
      "4 pulling\n",
      "18 pump\n",
      "2 pun\n",
      "4 purchase\n",
      "6 purchased\n",
      "7 pure\n",
      "2 purification\n",
      "2 purpose\n",
      "5 pushed\n",
      "2 pushy\n",
      "65 put\n",
      "2 puts\n",
      "7 putting\n",
      "4 quaint\n",
      "2 qualities\n",
      "84 quality\n",
      "29 queen\n",
      "4 queens\n",
      "7 question\n",
      "14 questions\n",
      "41 quick\n",
      "29 quickly\n",
      "57 quiet\n",
      "3 quieted\n",
      "2 quikbook\n",
      "114 quite\n",
      "4 quoted\n",
      "2 rack\n",
      "2 racks\n",
      "10 radio\n",
      "4 rain\n",
      "5 raised\n",
      "12 ran\n",
      "2 random\n",
      "4 rang\n",
      "6 range\n",
      "2 ranged\n",
      "2 ranges\n",
      "5 rare\n",
      "4 rarely\n",
      "92 rate\n",
      "7 rated\n",
      "24 rates\n",
      "50 rather\n",
      "15 rating\n",
      "4 ratings\n",
      "2 rationed\n",
      "2 ratty\n",
      "4 rave\n",
      "3 raved\n",
      "17 rd\n",
      "10 reach\n",
      "4 reached\n",
      "3 reaching\n",
      "36 read\n",
      "2 reader\n",
      "22 reading\n",
      "78 ready\n",
      "2 reaked\n",
      "26 real\n",
      "3 reality\n",
      "5 realize\n",
      "14 realized\n",
      "2 realizing\n",
      "247 really\n",
      "3 realy\n",
      "23 reason\n",
      "26 reasonable\n",
      "9 reasonably\n",
      "5 reasons\n",
      "3 reassured\n",
      "5 reccomend\n",
      "4 receipt\n",
      "13 receive\n",
      "51 received\n",
      "7 receiving\n",
      "25 recent\n",
      "111 recently\n",
      "53 reception\n",
      "19 receptionist\n",
      "3 receptionists\n",
      "2 receptions\n",
      "2 recession\n",
      "2 reciepts\n",
      "2 recieve\n",
      "4 recieved\n",
      "2 recognize\n",
      "237 recommend\n",
      "4 recommendation\n",
      "14 recommendations\n",
      "35 recommended\n",
      "7 recommending\n",
      "3 reconsider\n",
      "11 record\n",
      "2 recovering\n",
      "3 recreation\n",
      "5 rectify\n",
      "2 recycling\n",
      "20 red\n",
      "2 redecorated\n",
      "5 redeeming\n",
      "4 redone\n",
      "4 reduced\n",
      "5 reeked\n",
      "3 refer\n",
      "3 referred\n",
      "2 referring\n",
      "2 refill\n",
      "2 reflect\n",
      "2 reflected\n",
      "2 refresh\n",
      "3 refreshed\n",
      "4 refreshing\n",
      "2 refreshment\n",
      "10 refrigerator\n",
      "2 refuge\n",
      "15 refund\n",
      "2 refurbished\n",
      "18 refused\n",
      "6 regarding\n",
      "5 regardless\n",
      "2 regards\n",
      "38 regency\n",
      "2 register\n",
      "4 registered\n",
      "6 registration\n",
      "6 regret\n",
      "21 regular\n",
      "2 regularly\n",
      "3 related\n",
      "10 relatively\n",
      "2 relatives\n",
      "35 relax\n",
      "4 relaxation\n",
      "8 relaxed\n",
      "45 relaxing\n",
      "6 reliable\n",
      "2 relief\n",
      "2 relieve\n",
      "4 relieved\n",
      "5 reluctant\n",
      "3 reluctantly\n",
      "4 remainder\n",
      "2 remained\n",
      "3 remarkable\n",
      "2 remedy\n",
      "10 remember\n",
      "3 remembered\n",
      "3 remind\n",
      "5 reminded\n",
      "2 reminder\n",
      "2 remnants\n",
      "2 remodel\n",
      "7 remodeled\n",
      "13 remote\n",
      "3 remotely\n",
      "6 removed\n",
      "2 rendered\n",
      "17 renovated\n",
      "19 renovation\n",
      "13 renovations\n",
      "4 rent\n",
      "6 rental\n",
      "5 rented\n",
      "5 rep\n",
      "6 repair\n",
      "3 repaired\n",
      "2 repairs\n",
      "5 repeat\n",
      "2 repeated\n",
      "5 repeatedly\n",
      "5 replace\n",
      "10 replaced\n",
      "7 replacement\n",
      "5 replenished\n",
      "4 replied\n",
      "4 reply\n",
      "8 report\n",
      "12 reported\n",
      "3 reporting\n",
      "2 reports\n",
      "6 representative\n",
      "5 reputation\n",
      "42 request\n",
      "78 requested\n",
      "5 requesting\n",
      "15 requests\n",
      "5 required\n",
      "2 requires\n",
      "6 research\n",
      "2 resembled\n",
      "146 reservation\n",
      "51 reservations\n",
      "5 reserve\n",
      "44 reserved\n",
      "3 reserving\n",
      "2 residential\n",
      "4 resist\n",
      "9 resolve\n",
      "3 resolved\n",
      "7 resort\n",
      "2 resources\n",
      "10 respect\n",
      "2 respectful\n",
      "2 respite\n",
      "3 respond\n",
      "2 responded\n",
      "11 response\n",
      "2 responsibility\n",
      "8 responsive\n",
      "35 rest\n",
      "2 restaraunts\n",
      "178 restaurant\n",
      "90 restaurants\n",
      "2 rested\n",
      "5 restful\n",
      "2 resting\n",
      "7 restroom\n",
      "2 restuarant\n",
      "6 resturant\n",
      "4 result\n",
      "2 resulting\n",
      "2 retreat\n",
      "2 retrieved\n",
      "2 retrieving\n",
      "2 retro\n",
      "74 return\n",
      "46 returned\n",
      "23 returning\n",
      "2 reunion\n",
      "4 revealed\n",
      "2 reverse\n",
      "29 review\n",
      "2 reviewer\n",
      "75 reviews\n",
      "3 revisit\n",
      "4 rewards\n",
      "5 rex\n",
      "2 ribeye\n",
      "2 rice\n",
      "5 rich\n",
      "3 rid\n",
      "24 ride\n",
      "20 ridiculous\n",
      "4 ridiculously\n",
      "171 right\n",
      "3 ring\n",
      "2 rip\n",
      "2 ripped\n",
      "2 rise\n",
      "4 risk\n",
      "5 ritz\n",
      "2 ritzy\n",
      "64 river\n",
      "2 rm\n",
      "4 roach\n",
      "4 roaches\n",
      "6 road\n",
      "2 robert\n",
      "12 robes\n",
      "94 rock\n",
      "10 roll\n",
      "4 rollaway\n",
      "8 rolled\n",
      "5 romance\n",
      "24 romantic\n",
      "11 roof\n",
      "6 rooftop\n",
      "2262 room\n",
      "548 rooms\n",
      "2 roomservice\n",
      "7 roomy\n",
      "2 rose\n",
      "2 rotten\n",
      "5 rough\n",
      "4 round\n",
      "3 routine\n",
      "2 routing\n",
      "3 row\n",
      "3 rowdy\n",
      "2 royal\n",
      "10 royalty\n",
      "116 rude\n",
      "7 rudely\n",
      "4 rudeness\n",
      "2 rug\n",
      "5 ruin\n",
      "7 ruined\n",
      "2 rule\n",
      "25 run\n",
      "18 running\n",
      "2 runny\n",
      "4 runs\n",
      "15 rush\n",
      "5 rushed\n",
      "3 rusty\n",
      "3 ryan\n",
      "8 sad\n",
      "5 sadly\n",
      "17 safe\n",
      "2 safely\n",
      "2 safes\n",
      "2 safety\n",
      "134 said\n",
      "2 sake\n",
      "2 saks\n",
      "5 salad\n",
      "5 sales\n",
      "2 salon\n",
      "2 salts\n",
      "2 sample\n",
      "5 san\n",
      "5 sandwich\n",
      "19 sat\n",
      "1 satayed\n",
      "1 satelite\n",
      "4 satisfaction\n",
      "5 satisfactory\n",
      "1 satisfication\n",
      "11 satisfied\n",
      "1 satisfy\n",
      "21 saturday\n",
      "1 sauce\n",
      "3 sauna\n",
      "1 saunas\n",
      "1 sausage\n",
      "13 save\n",
      "9 saved\n",
      "1 saver\n",
      "3 saving\n",
      "1 savings\n",
      "1 savvy\n",
      "54 saw\n",
      "1 sax\n",
      "193 say\n",
      "23 saying\n",
      "8 says\n",
      "1 scaffolding\n",
      "4 scale\n",
      "1 scampered\n",
      "1 scampering\n",
      "1 scandanavian\n",
      "1 scant\n",
      "1 scape\n",
      "1 scar\n",
      "1 scarce\n",
      "2 scared\n",
      "1 scarves\n",
      "1 scary\n",
      "1 scattered\n",
      "1 scenario\n",
      "1 scenary\n",
      "5 scene\n",
      "2 scenery\n",
      "2 scenic\n",
      "4 scent\n",
      "4 schedule\n",
      "1 scheduled\n",
      "2 scheduling\n",
      "1 scherer\n",
      "1 schicago\n",
      "1 schmaltzy\n",
      "1 schnitzel\n",
      "4 school\n",
      "2 schrager\n",
      "3 science\n",
      "2 scoffed\n",
      "1 scoot\n",
      "1 scope\n",
      "2 scored\n",
      "1 scores\n",
      "2 scott\n",
      "1 scouring\n",
      "1 scout\n",
      "1 scouts\n",
      "1 scowled\n",
      "1 scramble\n",
      "2 scrambled\n",
      "1 scrap\n",
      "2 scrape\n",
      "1 scraped\n",
      "1 scraper\n",
      "1 scraping\n",
      "1 scraps\n",
      "1 scratched\n",
      "2 scratches\n",
      "1 scratching\n",
      "3 scratchy\n",
      "1 scream\n",
      "2 screaming\n",
      "1 screeching\n",
      "50 screen\n",
      "1 screened\n",
      "1 screens\n",
      "1 screw\n",
      "1 screwed\n",
      "1 screws\n",
      "1 scrubber\n",
      "1 scrubbing\n",
      "1 scrumptious\n",
      "1 scuffed\n",
      "1 sculptures\n",
      "3 scum\n",
      "1 scurried\n",
      "1 scurry\n",
      "2 scurrying\n",
      "1 seadog\n",
      "4 seafood\n",
      "2 seal\n",
      "2 sealed\n",
      "1 sean\n",
      "2 search\n",
      "4 searched\n",
      "2 searching\n",
      "1 searing\n",
      "7 sears\n",
      "3 season\n",
      "1 seasonal\n",
      "4 seasoned\n",
      "12 seasons\n",
      "13 seat\n",
      "2 seated\n",
      "7 seating\n",
      "4 seats\n",
      "1 seattle\n",
      "69 second\n",
      "4 secondly\n",
      "2 seconds\n",
      "4 section\n",
      "6 secure\n",
      "2 securing\n",
      "19 security\n",
      "89 see\n",
      "3 seedy\n",
      "20 seeing\n",
      "2 seek\n",
      "32 seem\n",
      "109 seemed\n",
      "1 seeming\n",
      "3 seemingly\n",
      "44 seems\n",
      "28 seen\n",
      "1 seer\n",
      "1 selcted\n",
      "6 select\n",
      "3 selected\n",
      "16 selection\n",
      "2 selections\n",
      "13 self\n",
      "1 selfpark\n",
      "2 sell\n",
      "1 selling\n",
      "2 sells\n",
      "1 selman\n",
      "4 seminar\n",
      "22 send\n",
      "1 sending\n",
      "2 sends\n",
      "7 sense\n",
      "2 senses\n",
      "1 sensibilities\n",
      "1 sensibility\n",
      "2 sensitive\n",
      "1 sensitivities\n",
      "2 sensors\n",
      "20 sent\n",
      "1 sentences\n",
      "1 seoul\n",
      "1 sep\n",
      "23 separate\n",
      "3 separated\n",
      "1 separately\n",
      "4 seperate\n",
      "1 sept\n",
      "13 september\n",
      "1 serene\n",
      "4 serenity\n",
      "3 series\n",
      "5 serious\n",
      "13 seriously\n",
      "13 serve\n",
      "30 served\n",
      "4 server\n",
      "9 servers\n",
      "6 serves\n",
      "647 service\n",
      "1 serviceable\n",
      "3 serviced\n",
      "37 services\n",
      "1 servicing\n",
      "5 serving\n",
      "2 session\n",
      "2 sessions\n",
      "1 seston\n",
      "45 set\n",
      "2 sets\n",
      "9 setting\n",
      "2 settings\n",
      "6 settle\n",
      "13 settled\n",
      "4 settling\n",
      "3 setup\n",
      "1 seveal\n",
      "2 seven\n",
      "1 seventh\n",
      "78 several\n",
      "2 severe\n",
      "9 severely\n",
      "1 severly\n",
      "2 sevice\n",
      "2 sex\n",
      "1 sexual\n",
      "4 sexy\n",
      "2 sf\n",
      "1 sh\n",
      "6 shabby\n",
      "1 shades\n",
      "1 shady\n",
      "1 shaft\n",
      "1 shake\n",
      "1 shaking\n",
      "1 shall\n",
      "1 shallow\n",
      "1 shambles\n",
      "5 shame\n",
      "1 shamed\n",
      "1 shameful\n",
      "26 shampoo\n",
      "1 shampooed\n",
      "2 shampoos\n",
      "6 shape\n",
      "2 shaped\n",
      "1 shards\n",
      "10 share\n",
      "5 shared\n",
      "3 sharing\n",
      "2 sharon\n",
      "3 sharp\n",
      "2 shaving\n",
      "3 shea\n",
      "3 sheas\n",
      "1 shed\n",
      "5 shedd\n",
      "1 sheen\n",
      "1 sheer\n",
      "5 sheet\n",
      "60 sheets\n",
      "3 shelf\n",
      "1 shells\n",
      "2 shelves\n",
      "1 shepard\n",
      "1 shepards\n",
      "1 shepherd\n",
      "56 sheraton\n",
      "2 sheratons\n",
      "1 shi\n",
      "2 shift\n",
      "1 shine\n",
      "1 shined\n",
      "4 shining\n",
      "1 ship\n",
      "1 shipped\n",
      "1 shit\n",
      "3 shock\n",
      "7 shocked\n",
      "1 shocker\n",
      "2 shocking\n",
      "1 shoddy\n",
      "1 shoe\n",
      "1 shoebox\n",
      "11 shoes\n",
      "1 shoeshine\n",
      "1 shoo\n",
      "1 shook\n",
      "1 shoot\n",
      "1 shooting\n",
      "16 shop\n",
      "1 shopped\n",
      "3 shopper\n",
      "1 shoppers\n",
      "114 shopping\n",
      "20 shops\n",
      "1 shore\n",
      "64 short\n",
      "2 shortage\n",
      "2 shortcomings\n",
      "2 shortly\n",
      "1 shorts\n",
      "3 shot\n",
      "3 shoulders\n",
      "2 shouting\n",
      "3 shoved\n",
      "38 show\n",
      "20 showed\n",
      "118 shower\n",
      "4 showerhead\n",
      "3 showering\n",
      "9 showers\n",
      "5 showing\n",
      "4 shown\n",
      "11 shows\n",
      "3 shrugged\n",
      "3 shuffle\n",
      "5 shula\n",
      "6 shut\n",
      "8 shuttle\n",
      "5 sick\n",
      "42 side\n",
      "5 sides\n",
      "3 sidewalk\n",
      "2 sighed\n",
      "14 sight\n",
      "14 sights\n",
      "10 sightseeing\n",
      "31 sign\n",
      "6 signal\n",
      "3 signature\n",
      "4 signed\n",
      "3 significant\n",
      "5 significantly\n",
      "3 signing\n",
      "4 signs\n",
      "2 sill\n",
      "16 similar\n",
      "2 similarly\n",
      "10 simple\n",
      "40 simply\n",
      "2 sinatra\n",
      "94 since\n",
      "2 sincerely\n",
      "14 single\n",
      "2 singles\n",
      "29 sink\n",
      "5 sinks\n",
      "6 sirens\n",
      "9 sister\n",
      "2 sisters\n",
      "25 sit\n",
      "30 site\n",
      "12 sites\n",
      "4 sits\n",
      "23 sitting\n",
      "10 situated\n",
      "28 situation\n",
      "7 six\n",
      "67 size\n",
      "31 sized\n",
      "2 skeptical\n",
      "4 skin\n",
      "2 skip\n",
      "3 skipped\n",
      "2 skipping\n",
      "3 sky\n",
      "5 skyline\n",
      "3 slam\n",
      "3 slammed\n",
      "2 slap\n",
      "12 sleek\n",
      "76 sleep\n",
      "12 sleeper\n",
      "15 sleeping\n",
      "4 sleepless\n",
      "24 slept\n",
      "2 slice\n",
      "2 slide\n",
      "4 sliding\n",
      "5 slight\n",
      "8 slightly\n",
      "1 slimy\n",
      "3 slip\n",
      "10 slippers\n",
      "2 slippery\n",
      "1 slipping\n",
      "2 sliver\n",
      "1 sloppy\n",
      "1 slot\n",
      "45 slow\n",
      "2 slowed\n",
      "2 slower\n",
      "2 slowly\n",
      "3 slumber\n",
      "1 slumming\n",
      "2 smacking\n",
      "163 small\n",
      "24 smaller\n",
      "4 smallest\n",
      "55 smell\n",
      "58 smelled\n",
      "4 smelling\n",
      "3 smells\n",
      "5 smelly\n",
      "9 smile\n",
      "3 smiles\n",
      "6 smiling\n",
      "48 smoke\n",
      "4 smoked\n",
      "3 smoker\n",
      "2 smokers\n",
      "2 smokey\n",
      "68 smoking\n",
      "8 smooth\n",
      "4 smoothly\n",
      "1 smudge\n",
      "1 smudges\n",
      "8 snack\n",
      "1 snacking\n",
      "12 snacks\n",
      "1 snagged\n",
      "1 snaps\n",
      "1 sneak\n",
      "1 sneek\n",
      "2 sneezing\n",
      "1 snickered\n",
      "1 snickers\n",
      "1 snide\n",
      "1 sniping\n",
      "1 snippets\n",
      "1 snippy\n",
      "2 snobbery\n",
      "1 snobbishness\n",
      "2 snobby\n",
      "1 snooping\n",
      "6 snooty\n",
      "1 snooze\n",
      "1 snot\n",
      "1 snotty\n",
      "3 snow\n",
      "2 snubbed\n",
      "1 snubery\n",
      "1 snug\n",
      "2 soak\n",
      "5 soaking\n",
      "20 soap\n",
      "4 soaps\n",
      "3 social\n",
      "5 soda\n",
      "17 sofa\n",
      "3 sofabed\n",
      "2 sofas\n",
      "64 sofitel\n",
      "19 soft\n",
      "3 softest\n",
      "2 softiel\n",
      "2 software\n",
      "2 soiled\n",
      "9 sold\n",
      "4 soldier\n",
      "4 solely\n",
      "6 solid\n",
      "2 solution\n",
      "3 somebody\n",
      "8 somehow\n",
      "93 someone\n",
      "7 someplace\n",
      "84 something\n",
      "6 sometimes\n",
      "25 somewhat\n",
      "31 somewhere\n",
      "26 son\n",
      "40 soon\n",
      "2 sooner\n",
      "3 soooo\n",
      "2 soothing\n",
      "6 sophisticated\n",
      "3 sophistication\n",
      "6 sorely\n",
      "16 sorry\n",
      "19 sort\n",
      "2 sorted\n",
      "3 sorts\n",
      "26 sound\n",
      "14 sounded\n",
      "1 sounding\n",
      "2 soundly\n",
      "1 soundproofing\n",
      "3 sounds\n",
      "7 soup\n",
      "1 sour\n",
      "1 source\n",
      "1 soured\n",
      "18 south\n",
      "1 sox\n",
      "1 sp\n",
      "62 spa\n",
      "35 space\n",
      "2 spaces\n",
      "1 spacey\n",
      "1 spacing\n",
      "91 spacious\n",
      "1 spaffina\n",
      "1 spake\n",
      "1 spanish\n",
      "1 spanking\n",
      "4 spare\n",
      "1 sparkled\n",
      "4 sparkling\n",
      "1 sparsely\n",
      "16 speak\n",
      "2 speaker\n",
      "3 speakers\n",
      "3 speaking\n",
      "1 specacular\n",
      "64 special\n",
      "1 specialist\n",
      "2 specially\n",
      "4 specials\n",
      "1 specialty\n",
      "2 specific\n",
      "9 specifically\n",
      "2 specifics\n",
      "1 spectacle\n",
      "13 spectacular\n",
      "1 spectacularly\n",
      "23 speed\n",
      "1 speeds\n",
      "1 speedy\n",
      "1 spell\n",
      "2 spelled\n",
      "47 spend\n",
      "19 spending\n",
      "1 spends\n",
      "58 spent\n",
      "1 spicy\n",
      "1 spiderwebs\n",
      "2 spilled\n",
      "1 spit\n",
      "6 spite\n",
      "1 spitting\n",
      "1 splash\n",
      "1 splashed\n",
      "1 splashes\n",
      "1 splendido\n",
      "1 splinters\n",
      "3 split\n",
      "1 splurge\n",
      "1 spoil\n",
      "1 spoiled\n",
      "12 spoke\n",
      "2 spoken\n",
      "1 spolied\n",
      "1 spontaneous\n",
      "9 spoon\n",
      "1 sporting\n",
      "2 sports\n",
      "11 spot\n",
      "14 spotless\n",
      "2 spotlessly\n",
      "14 spots\n",
      "1 spotting\n",
      "1 spotty\n",
      "1 sprawled\n",
      "1 sprawling\n",
      "4 spray\n",
      "1 sprayed\n",
      "4 spread\n",
      "1 spreading\n",
      "1 spree\n",
      "5 spring\n",
      "1 springs\n",
      "1 springy\n",
      "1 spur\n",
      "4 sq\n",
      "1 sqft\n",
      "4 square\n",
      "1 squeaking\n",
      "1 squealing\n",
      "1 squeals\n",
      "1 squeezed\n",
      "1 ss\n",
      "13 st\n",
      "1 sta\n",
      "1 stacked\n",
      "1 stadium\n",
      "668 staff\n",
      "10 staffed\n",
      "1 staffing\n",
      "2 staffs\n",
      "1 stage\n",
      "13 stain\n",
      "19 stained\n",
      "1 stainless\n",
      "20 stains\n",
      "2 stair\n",
      "2 staircase\n",
      "9 stairs\n",
      "1 stairwell\n",
      "1 stairwells\n",
      "13 stale\n",
      "2 stall\n",
      "14 stand\n",
      "31 standard\n",
      "11 standards\n",
      "1 standby\n",
      "5 standing\n",
      "1 standoffish\n",
      "1 stands\n",
      "3 stank\n",
      "98 star\n",
      "19 starbucks\n",
      "1 starched\n",
      "2 stare\n",
      "1 stared\n",
      "1 stares\n",
      "1 staring\n",
      "6 stark\n",
      "1 starpoints\n",
      "25 stars\n",
      "35 start\n",
      "32 started\n",
      "2 starters\n",
      "5 starting\n",
      "4 starts\n",
      "3 starving\n",
      "5 starwood\n",
      "1 stash\n",
      "23 state\n",
      "13 stated\n",
      "3 stately\n",
      "7 statement\n",
      "3 states\n",
      "1 static\n",
      "5 stating\n",
      "18 station\n",
      "1 stations\n",
      "1 statistical\n",
      "1 stature\n",
      "1042 stay\n",
      "536 stayed\n",
      "1 stayfittm\n",
      "223 staying\n",
      "15 stays\n",
      "2 steady\n",
      "12 steak\n",
      "9 steakhouse\n",
      "4 steaks\n",
      "7 steal\n",
      "1 stealing\n",
      "1 steamer\n",
      "2 steel\n",
      "3 steep\n",
      "1 steer\n",
      "1 stella\n",
      "1 stellar\n",
      "10 step\n",
      "1 stepdad\n",
      "2 stephanie\n",
      "6 stepped\n",
      "1 steppers\n",
      "3 stepping\n",
      "7 steps\n",
      "4 stereo\n",
      "2 sterile\n",
      "3 sterling\n",
      "1 stetson\n",
      "1 steven\n",
      "2 stick\n",
      "1 stickers\n",
      "1 stickler\n",
      "1 sticks\n",
      "2 sticky\n",
      "4 stiff\n",
      "1 stiffness\n",
      "1 stifling\n",
      "104 still\n",
      "1 stinch\n",
      "1 sting\n",
      "1 stinking\n",
      "1 stirrers\n",
      "1 stock\n",
      "14 stocked\n",
      "2 stocking\n",
      "2 stoked\n",
      "1 stole\n",
      "2 stolen\n",
      "1 stomped\n",
      "1 stone\n",
      "9 stood\n",
      "28 stop\n",
      "16 stopped\n",
      "1 stopper\n",
      "6 stops\n",
      "5 storage\n",
      "13 store\n",
      "7 stores\n",
      "1 storey\n",
      "1 storied\n",
      "5 stories\n",
      "2 storing\n",
      "2 storm\n",
      "1 stormed\n",
      "7 story\n",
      "3 stove\n",
      "9 straight\n",
      "1 straighten\n",
      "1 straiten\n",
      "1 stranded\n",
      "4 strange\n",
      "2 strangely\n",
      "1 strangers\n",
      "1 strap\n",
      "4 strawberries\n",
      "1 stray\n",
      "1 streaked\n",
      "1 streamlined\n",
      "84 street\n",
      "4 streets\n",
      "1 streetside\n",
      "1 strength\n",
      "7 stress\n",
      "1 stressed\n",
      "4 stressful\n",
      "3 strewn\n",
      "1 strict\n",
      "1 strictly\n",
      "1 strike\n",
      "2 striking\n",
      "1 stringers\n",
      "2 strip\n",
      "1 striped\n",
      "1 strives\n",
      "1 stroll\n",
      "1 strollers\n",
      "1 strolling\n",
      "7 strong\n",
      "1 strongest\n",
      "9 strongly\n",
      "3 structure\n",
      "1 strudel\n",
      "1 struggle\n",
      "2 struggling\n",
      "1 strut\n",
      "19 stuck\n",
      "1 stucture\n",
      "1 student\n",
      "2 students\n",
      "2 studio\n",
      "3 study\n",
      "18 stuff\n",
      "3 stuffed\n",
      "6 stuffy\n",
      "1 stumbled\n",
      "1 stumbling\n",
      "3 stunned\n",
      "12 stunning\n",
      "2 stupid\n",
      "1 stupidity\n",
      "24 style\n",
      "2 styles\n",
      "1 stylings\n",
      "15 stylish\n",
      "1 stylishly\n",
      "1 styx\n",
      "12 sub\n",
      "1 suberb\n",
      "1 sublime\n",
      "1 submerge\n",
      "3 subpar\n",
      "1 subroofer\n",
      "1 subsequently\n",
      "2 substantial\n",
      "1 subtle\n",
      "6 suburbs\n",
      "11 subway\n",
      "2 success\n",
      "1 successfully\n",
      "1 succession\n",
      "1 succulent\n",
      "2 sucked\n",
      "1 suckish\n",
      "2 sudden\n",
      "2 suddenly\n",
      "1 suede\n",
      "1 suffer\n",
      "2 suffered\n",
      "4 suffice\n",
      "3 sufficient\n",
      "1 suffocated\n",
      "2 sugar\n",
      "15 suggest\n",
      "20 suggested\n",
      "1 suggesting\n",
      "3 suggestion\n",
      "10 suggestions\n",
      "5 suit\n",
      "6 suitcase\n",
      "2 suitcases\n",
      "139 suite\n",
      "2 suited\n",
      "76 suites\n",
      "4 suits\n",
      "1 sulked\n",
      "1 sullivans\n",
      "1 sully\n",
      "2 sum\n",
      "5 summary\n",
      "1 summation\n",
      "1 summed\n",
      "16 summer\n",
      "1 summon\n",
      "6 sun\n",
      "17 sunday\n",
      "2 sundecks\n",
      "2 sunglasses\n",
      "3 sunlight\n",
      "2 sunny\n",
      "33 super\n",
      "27 superb\n",
      "2 superbly\n",
      "2 superficial\n",
      "15 superior\n",
      "2 supervisor\n",
      "7 supper\n",
      "4 supplied\n",
      "3 supplies\n",
      "5 supply\n",
      "3 support\n",
      "12 suppose\n",
      "42 supposed\n",
      "11 supposedly\n",
      "80 sure\n",
      "8 surely\n",
      "2 surface\n",
      "2 surgery\n",
      "4 surly\n",
      "3 surpassed\n",
      "16 surprise\n",
      "31 surprised\n",
      "5 surprising\n",
      "3 surprisingly\n",
      "2 surround\n",
      "5 surrounded\n",
      "7 surrounding\n",
      "4 surveillance\n",
      "2 sushi\n",
      "3 suspect\n",
      "4 sutton\n",
      "2 suv\n",
      "3 swear\n",
      "2 sweat\n",
      "7 sweet\n",
      "2 sweets\n",
      "3 swept\n",
      "8 swim\n",
      "16 swimming\n",
      "2 swisshotel\n",
      "53 swissotel\n",
      "16 switch\n",
      "11 switched\n",
      "2 sylvia\n",
      "2 sympathetic\n",
      "2 sympathy\n",
      "30 system\n",
      "2 systems\n",
      "4 ta\n",
      "23 table\n",
      "7 tables\n",
      "6 tacky\n",
      "3 tag\n",
      "2 tainted\n",
      "142 take\n",
      "31 taken\n",
      "10 takes\n",
      "23 taking\n",
      "6 talbot\n",
      "68 talbott\n",
      "19 talk\n",
      "7 talked\n",
      "27 talking\n",
      "3 tall\n",
      "2 tank\n",
      "4 tap\n",
      "2 target\n",
      "2 task\n",
      "21 taste\n",
      "13 tasted\n",
      "6 tastefully\n",
      "3 tasting\n",
      "5 tasty\n",
      "2 tattered\n",
      "8 tax\n",
      "7 taxes\n",
      "21 taxi\n",
      "2 taxis\n",
      "14 tea\n",
      "2 team\n",
      "2 teams\n",
      "5 tech\n",
      "2 technical\n",
      "2 technology\n",
      "5 teenage\n",
      "5 teenager\n",
      "3 teenagers\n",
      "2 teens\n",
      "24 television\n",
      "5 televisions\n",
      "43 tell\n",
      "10 telling\n",
      "3 tells\n",
      "6 temp\n",
      "13 temperature\n",
      "2 tempted\n",
      "14 ten\n",
      "2 tend\n",
      "2 tenth\n",
      "10 terms\n",
      "10 terrace\n",
      "41 terrible\n",
      "8 terribly\n",
      "14 terrific\n",
      "2 terror\n",
      "3 terry\n",
      "2 test\n",
      "4 texting\n",
      "93 th\n",
      "24 thank\n",
      "6 thankfully\n",
      "22 thanks\n",
      "3 thanksgiving\n",
      "4 thats\n",
      "15 theater\n",
      "3 theaters\n",
      "8 theatre\n",
      "3 theatres\n",
      "5 theme\n",
      "4 themed\n",
      "2 therapy\n",
      "5 therefore\n",
      "3 thereof\n",
      "2 theres\n",
      "4 thick\n",
      "5 thier\n",
      "25 thin\n",
      "83 thing\n",
      "83 things\n",
      "108 think\n",
      "9 thinking\n",
      "3 thinks\n",
      "17 third\n",
      "3 thirdly\n",
      "2 thirty\n",
      "3 thorough\n",
      "13 thoroughly\n",
      "121 though\n",
      "85 thought\n",
      "3 thread\n",
      "3 threatened\n",
      "73 three\n",
      "3 threw\n",
      "2 thrilled\n",
      "3 throbbing\n",
      "36 throughout\n",
      "10 throw\n",
      "2 throwback\n",
      "4 thrown\n",
      "14 thru\n",
      "7 thumbs\n",
      "8 thursday\n",
      "3 thus\n",
      "6 ticket\n",
      "6 tickets\n",
      "8 tidy\n",
      "2 tied\n",
      "2 til\n",
      "9 tile\n",
      "3 tiled\n",
      "2 tiles\n",
      "4 till\n",
      "2 tim\n",
      "400 time\n",
      "4 timely\n",
      "76 times\n",
      "2 timetable\n",
      "37 tiny\n",
      "23 tip\n",
      "2 tipped\n",
      "6 tips\n",
      "42 tired\n",
      "6 toast\n",
      "7 today\n",
      "2 toe\n",
      "13 together\n",
      "59 toilet\n",
      "11 toiletries\n",
      "168 told\n",
      "4 tolerable\n",
      "2 tolerate\n",
      "3 toliet\n",
      "2 tomato\n",
      "3 ton\n",
      "5 tone\n",
      "3 tones\n",
      "2 toni\n",
      "6 tons\n",
      "164 took\n",
      "2 tools\n",
      "3 toothpaste\n",
      "93 top\n",
      "2 topped\n",
      "4 tops\n",
      "6 torn\n",
      "3 tossed\n",
      "16 total\n",
      "25 totally\n",
      "25 touch\n",
      "5 touched\n",
      "10 touches\n",
      "3 tough\n",
      "14 tour\n",
      "3 touring\n",
      "11 tourist\n",
      "6 tourists\n",
      "2 touristy\n",
      "2 tours\n",
      "3 touted\n",
      "6 toward\n",
      "9 towards\n",
      "9 towel\n",
      "84 towels\n",
      "64 tower\n",
      "2 towering\n",
      "34 towers\n",
      "58 town\n",
      "2 towners\n",
      "8 track\n",
      "3 trade\n",
      "2 trader\n",
      "7 traditional\n",
      "21 traffic\n",
      "19 train\n",
      "6 trained\n",
      "9 training\n",
      "4 trains\n",
      "2 traits\n",
      "4 tranquility\n",
      "3 transfer\n",
      "7 transferred\n",
      "3 transit\n",
      "2 transport\n",
      "16 transportation\n",
      "10 trash\n",
      "75 travel\n",
      "15 traveled\n",
      "23 traveler\n",
      "13 travelers\n",
      "31 traveling\n",
      "2 travelled\n",
      "3 traveller\n",
      "2 travellers\n",
      "10 travelling\n",
      "7 travels\n",
      "7 travelzoo\n",
      "2 tray\n",
      "3 trays\n",
      "7 treadmill\n",
      "5 treadmills\n",
      "2 treasure\n",
      "24 treat\n",
      "42 treated\n",
      "2 treating\n",
      "9 treatment\n",
      "5 treatments\n",
      "5 treats\n",
      "3 tree\n",
      "5 tremendous\n",
      "13 trendy\n",
      "5 tribune\n",
      "2 trickle\n",
      "48 tried\n",
      "2 tries\n",
      "181 trip\n",
      "2 tripadvisor\n",
      "4 triple\n",
      "14 trips\n",
      "3 trolley\n",
      "21 trouble\n",
      "2 troubles\n",
      "2 truck\n",
      "2 trucks\n",
      "20 true\n",
      "3 truely\n",
      "45 truly\n",
      "4 trump\n",
      "5 trust\n",
      "8 truth\n",
      "68 try\n",
      "38 trying\n",
      "52 tub\n",
      "2 tubs\n",
      "2 tucked\n",
      "2 tuesday\n",
      "2 turd\n",
      "35 turn\n",
      "7 turndown\n",
      "33 turned\n",
      "4 turning\n",
      "8 turns\n",
      "107 tv\n",
      "9 tvs\n",
      "2 twelveth\n",
      "10 twenty\n",
      "34 twice\n",
      "4 twin\n",
      "249 two\n",
      "29 type\n",
      "6 types\n",
      "10 typical\n",
      "2 typically\n",
      "2 typing\n",
      "2 ugh\n",
      "7 ugly\n",
      "2 uk\n",
      "2 ultimate\n",
      "3 ultimately\n",
      "3 ultra\n",
      "4 umbrella\n",
      "15 unable\n",
      "7 unacceptable\n",
      "2 unaccomodating\n",
      "5 unavailable\n",
      "2 unaware\n",
      "5 unbeatable\n",
      "4 unbelievable\n",
      "2 unbelievably\n",
      "2 uncaring\n",
      "4 unclean\n",
      "31 uncomfortable\n",
      "4 uncomfortably\n",
      "5 undergoing\n",
      "3 underground\n",
      "2 underneath\n",
      "6 understaffed\n",
      "25 understand\n",
      "2 understatement\n",
      "4 underwhelming\n",
      "5 unexpected\n",
      "2 unfailingly\n",
      "2 unfinished\n",
      "7 unfortunate\n",
      "50 unfortunately\n",
      "14 unfriendly\n",
      "10 unhappy\n",
      "12 unhelpful\n",
      "2 uniform\n",
      "2 uniformly\n",
      "3 unimpressed\n",
      "3 unimpressive\n",
      "2 uninspired\n",
      "4 uninterested\n",
      "3 uninviting\n",
      "11 unique\n",
      "9 unit\n",
      "2 united\n",
      "17 unless\n",
      "4 unlike\n",
      "3 unload\n",
      "2 unmade\n",
      "2 unpacking\n",
      "13 unpleasant\n",
      "8 unprofessional\n",
      "6 unreasonable\n",
      "2 unresponsive\n",
      "2 unsanitary\n",
      "4 unsatisfactory\n",
      "4 unsatisfied\n",
      "2 untill\n",
      "5 unusual\n",
      "2 unusually\n",
      "2 unwelcome\n",
      "2 unwilling\n",
      "3 unwind\n",
      "3 upbeat\n",
      "4 upcharge\n",
      "3 upcoming\n",
      "5 update\n",
      "16 updated\n",
      "9 updating\n",
      "37 upgrade\n",
      "34 upgraded\n",
      "2 upgrades\n",
      "2 upgrading\n",
      "2 upholstered\n",
      "105 upon\n",
      "9 upper\n",
      "2 ups\n",
      "30 upscale\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9 upset\n",
      "6 upstairs\n",
      "5 urban\n",
      "3 urine\n",
      "466 us\n",
      "3 usa\n",
      "3 usage\n",
      "3 usd\n",
      "114 use\n",
      "78 used\n",
      "2 user\n",
      "2 uses\n",
      "27 using\n",
      "15 usual\n",
      "20 usually\n",
      "2 utilize\n",
      "2 utilized\n",
      "2 utmost\n",
      "2 vacant\n",
      "58 vacation\n",
      "4 vacuum\n",
      "4 vacuumed\n",
      "57 valet\n",
      "7 valets\n",
      "2 valuables\n",
      "30 value\n",
      "2 valued\n",
      "2 van\n",
      "3 vanity\n",
      "9 variety\n",
      "7 various\n",
      "3 vegas\n",
      "2 vehicle\n",
      "5 vending\n",
      "3 vent\n",
      "2 venting\n",
      "3 vents\n",
      "3 venue\n",
      "4 verify\n",
      "2 versed\n",
      "11 via\n",
      "2 vibe\n",
      "3 vicinity\n",
      "2 victor\n",
      "2 victorian\n",
      "5 video\n",
      "203 view\n",
      "2 viewing\n",
      "61 views\n",
      "4 virtually\n",
      "5 visible\n",
      "122 visit\n",
      "22 visited\n",
      "49 visiting\n",
      "4 visitor\n",
      "3 visitors\n",
      "5 visits\n",
      "4 voice\n",
      "2 voiced\n",
      "2 voices\n",
      "3 volume\n",
      "4 vomit\n",
      "4 voucher\n",
      "3 vouchers\n",
      "2 vs\n",
      "2 wacker\n",
      "2 waffle\n",
      "137 wait\n",
      "26 waited\n",
      "11 waiter\n",
      "3 waiters\n",
      "53 waiting\n",
      "5 waitress\n",
      "3 waits\n",
      "3 waived\n",
      "11 wake\n",
      "2 wakeup\n",
      "2 waking\n",
      "112 walk\n",
      "2 walkable\n",
      "75 walked\n",
      "101 walking\n",
      "51 wall\n",
      "3 wallet\n",
      "12 wallpaper\n",
      "53 walls\n",
      "2 wander\n",
      "124 want\n",
      "81 wanted\n",
      "13 wanting\n",
      "10 wants\n",
      "42 warm\n",
      "2 warmer\n",
      "7 warmly\n",
      "4 warmth\n",
      "5 warned\n",
      "4 warning\n",
      "7 wash\n",
      "6 washed\n",
      "2 washington\n",
      "2 washroom\n",
      "7 wasnt\n",
      "20 waste\n",
      "3 wastebasket\n",
      "19 watch\n",
      "5 watched\n",
      "10 watching\n",
      "159 water\n",
      "4 waterfront\n",
      "153 way\n",
      "2 ways\n",
      "4 weak\n",
      "7 wear\n",
      "2 wearing\n",
      "12 weather\n",
      "7 web\n",
      "78 website\n",
      "3 websites\n",
      "50 wedding\n",
      "2 weddings\n",
      "2 wednesday\n",
      "2 wee\n",
      "75 week\n",
      "186 weekend\n",
      "8 weekends\n",
      "26 weeks\n",
      "2 weight\n",
      "3 weights\n",
      "4 weird\n",
      "31 welcome\n",
      "7 welcomed\n",
      "20 welcoming\n",
      "288 well\n",
      "200 went\n",
      "3 west\n",
      "2 western\n",
      "7 westin\n",
      "16 wet\n",
      "10 whatever\n",
      "5 whatsoever\n",
      "2 wheelchair\n",
      "10 whenever\n",
      "11 whether\n",
      "3 whilst\n",
      "2 whim\n",
      "3 whistle\n",
      "2 whistled\n",
      "22 white\n",
      "47 whole\n",
      "40 wi\n",
      "4 wicked\n",
      "8 wide\n",
      "138 wife\n",
      "44 wifi\n",
      "15 willing\n",
      "4 wind\n",
      "46 window\n",
      "33 windows\n",
      "21 windy\n",
      "65 wine\n",
      "2 wines\n",
      "4 winning\n",
      "8 winter\n",
      "3 wire\n",
      "4 wired\n",
      "34 wireless\n",
      "2 wise\n",
      "26 wish\n",
      "6 wished\n",
      "2 wishing\n",
      "71 within\n",
      "81 without\n",
      "2 witnessed\n",
      "2 woefully\n",
      "18 woke\n",
      "4 woken\n",
      "25 woman\n",
      "7 women\n",
      "6 wonder\n",
      "148 wonderful\n",
      "2 wonderfull\n",
      "5 wonderfully\n",
      "3 wondering\n",
      "5 wont\n",
      "7 wood\n",
      "2 wooden\n",
      "12 word\n",
      "8 words\n",
      "128 work\n",
      "22 worked\n",
      "6 worker\n",
      "11 workers\n",
      "46 working\n",
      "30 workout\n",
      "8 works\n",
      "30 world\n",
      "24 worn\n",
      "11 worried\n",
      "2 worry\n",
      "2 worrying\n",
      "22 worse\n",
      "62 worst\n",
      "81 worth\n",
      "2 worthy\n",
      "2 woudl\n",
      "763 would\n",
      "2 wouldnt\n",
      "16 wow\n",
      "2 wowed\n",
      "2 wrap\n",
      "2 wrapped\n",
      "3 wrigley\n",
      "2 wrinkled\n",
      "20 write\n",
      "7 writing\n",
      "9 written\n",
      "51 wrong\n",
      "7 wrote\n",
      "8 yeah\n",
      "65 year\n",
      "2 yearly\n",
      "52 years\n",
      "10 yelling\n",
      "10 yellow\n",
      "3 yelp\n",
      "2 yep\n",
      "30 yes\n",
      "2 yesterday\n",
      "51 yet\n",
      "6 yoga\n",
      "3 yogurt\n",
      "7 york\n",
      "14 young\n",
      "5 younger\n",
      "2 youve\n",
      "3 yuck\n",
      "5 yummy\n",
      "7 zest\n",
      "2 zone\n",
      "2 zoo\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Sum up the counts of each vocabulary word\n",
    "dist = np.sum(train_data_features, axis=0)\n",
    "\n",
    "# For each, print the vocabulary word and the number of times it \n",
    "# appears in the training set\n",
    "for tag, count in zip(vocab, dist):\n",
    "    print(count, tag)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training the random forest...\n"
     ]
    }
   ],
   "source": [
    "print(\"Training the random forest...\")\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "# Initialize a Random Forest classifier with 100 trees\n",
    "forest = RandomForestClassifier(n_estimators = 100) \n",
    "\n",
    "# Fit the forest to the training set, using the bag of words as \n",
    "# features and the sentiment labels as the response variable\n",
    "#\n",
    "# This may take a few minutes to run\n",
    "forest = forest.fit( train_data_features, train[\"polarity\"] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(320, 7)\n",
      "Cleaning and parsing the test set movie reviews...\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/bs4/__init__.py:181: UserWarning: No parser was explicitly specified, so I'm using the best available HTML parser for this system (\"lxml\"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently.\n",
      "\n",
      "The code that caused this warning is on line 193 of the file /anaconda3/lib/python3.6/runpy.py. To get rid of this warning, change code that looks like this:\n",
      "\n",
      " BeautifulSoup(YOUR_MARKUP})\n",
      "\n",
      "to this:\n",
      "\n",
      " BeautifulSoup(YOUR_MARKUP, \"lxml\")\n",
      "\n",
      "  markup_type=markup_type))\n"
     ]
    }
   ],
   "source": [
    "# Read the test data\n",
    "test = test\n",
    "\n",
    "# Verify that there are 25,000 rows and 2 columns\n",
    "print(test.shape)\n",
    "\n",
    "# Create an empty list and append the clean reviews one by one\n",
    "num_reviews = len(test[\"text\"])\n",
    "clean_test_reviews = [] \n",
    "\n",
    "print(\"Cleaning and parsing the test set movie reviews...\\n\")\n",
    "for i in range(0,num_reviews):\n",
    "    if( (i+1) % 1000 == 0 ):\n",
    "        print(\"Review %d of %d\\n\" % (i+1, num_reviews))\n",
    "    clean_review = review_to_words( test[\"text\"][i] )\n",
    "    clean_test_reviews.append( clean_review )\n",
    "\n",
    "# Get a bag of words for the test set, and convert to a numpy array\n",
    "test_data_features = vectorizer.transform(clean_test_reviews)\n",
    "test_data_features = test_data_features.toarray()\n",
    "\n",
    "# Use the random forest to make sentiment label predictions\n",
    "result = forest.predict(test_data_features)\n",
    "\n",
    "# Copy the results to a pandas dataframe with an \"id\" column and\n",
    "# a \"sentiment\" column\n",
    "output = pd.DataFrame( data={\"actual value\":test[\"polarity\"], \"polarity\":result} )\n",
    "\n",
    "# Use pandas to write the comma-separated output file\n",
    "#output.to_csv( \"Bag_of_Words_model.csv\", index=False, quoting=3 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>actual value</th>\n",
       "      <th>polarity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
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       "      <th>1</th>\n",
       "      <td>positive</td>\n",
       "      <td>negative</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>negative</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>positive</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>291</th>\n",
       "      <td>negative</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>292</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>293</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>294</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>295</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>296</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>298</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>301</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>302</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>303</th>\n",
       "      <td>positive</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>305</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>306</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>307</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>308</th>\n",
       "      <td>negative</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>309</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>310</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>315</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>316</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>318</th>\n",
       "      <td>negative</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319</th>\n",
       "      <td>positive</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>320 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    actual value  polarity\n",
       "0       positive  positive\n",
       "1       positive  negative\n",
       "2       positive  positive\n",
       "3       positive  positive\n",
       "4       negative  negative\n",
       "5       negative  negative\n",
       "6       negative  negative\n",
       "7       positive  positive\n",
       "8       positive  positive\n",
       "9       negative  negative\n",
       "10      positive  positive\n",
       "11      negative  positive\n",
       "12      negative  negative\n",
       "13      positive  positive\n",
       "14      negative  negative\n",
       "15      positive  positive\n",
       "16      positive  positive\n",
       "17      positive  positive\n",
       "18      positive  negative\n",
       "19      negative  negative\n",
       "20      positive  positive\n",
       "21      positive  positive\n",
       "22      positive  positive\n",
       "23      negative  negative\n",
       "24      negative  negative\n",
       "25      negative  negative\n",
       "26      positive  positive\n",
       "27      negative  negative\n",
       "28      negative  negative\n",
       "29      positive  positive\n",
       "..           ...       ...\n",
       "290     positive  positive\n",
       "291     negative  positive\n",
       "292     positive  positive\n",
       "293     positive  positive\n",
       "294     positive  positive\n",
       "295     positive  positive\n",
       "296     negative  negative\n",
       "297     positive  positive\n",
       "298     positive  positive\n",
       "299     negative  negative\n",
       "300     negative  negative\n",
       "301     positive  positive\n",
       "302     negative  negative\n",
       "303     positive  negative\n",
       "304     negative  negative\n",
       "305     negative  negative\n",
       "306     negative  negative\n",
       "307     positive  positive\n",
       "308     negative  positive\n",
       "309     positive  positive\n",
       "310     negative  negative\n",
       "311     positive  positive\n",
       "312     negative  negative\n",
       "313     positive  positive\n",
       "314     negative  negative\n",
       "315     negative  negative\n",
       "316     positive  positive\n",
       "317     positive  positive\n",
       "318     negative  negative\n",
       "319     positive  positive\n",
       "\n",
       "[320 rows x 2 columns]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "count = 0\n",
    "for i in range(0,320):\n",
    "    if output['actual value'][i] == output['polarity'][i]:\n",
    "        count = count + 1\n",
    "#print(count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.928125\n"
     ]
    }
   ],
   "source": [
    "print(count/320)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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